1. ETL Development

• Design, develop, and maintain end-to-end ETL/ELT processes using Azure Data Factory (ADF) and Azure Databricks.
• Write complex, high-performance T-SQL queries, stored procedures, and functions to transform raw data into actionable insights. Optimize data loads for performance and scalability within Azure SQL Database and Synapse Analytics.

2. Quality Assurance & Testing

• Develop and execute comprehensive Data Validation scripts to check for data completeness, transformation logic, and referential integrity. Conduct Source-to-Target mapping validation and performance testing on large datasets. Identify, document, and track data anomalies and bugs, working closely with the engineering team to resolve bottlenecks.

3. Infrastructure & Collaboration

• Work within an Agile environment, collaborating with Data Architects and Business Analysts to understand requirements. Manage version control and CI/CD deployments using Azure DevOps. Monitor pipeline health and set up automated alerts for failure or data drift.

Technical Requirements

SQL Mastery: Deep expertise in SQL (T-SQL/PL-SQL) for data manipulation, optimization, and complex joins.

Azure Data Stack: Hands-on experience with Azure Data Factory, Azure Data Lake Storage (ADLS), and Azure SQL Database. (Knowledge of Databricks/PySpark is a major plus).

Testing Tooling: Experience with data testing tools (e.g., dbt, Great Expectations) or custom Python/SQL testing scripts.

Cloud Infrastructure: Understanding of Azure environment security, Managed Identities, and Key Vaults.

Education: Degree in Computer Science, Information Technology, or a related field, plus 3–5 years of relevant experience.

Job Summary:

We are seeking a Data Analyst to support product decision-making through experimentation, data analysis, and reporting. This role will work closely with product and cross-functional teams to drive data-informed improvements and optimize product performance.

Job Responsibilities:

A/B Testing & Experimentation

• Design, execute, and analyze A/B tests to evaluate BT product features and optimizations
• Partner with the BT Product Manager to define success metrics and measurement frameworks
• Document testing methodologies, learnings, and best practices

BAU Data Analysis & Reporting

• Analyze and report on core BT product metrics, including DAU/MAU and app downloads, etc.
• Build dashboards and reports to track product health and performance trends
• Provide regular data updates to support product planning and decision-making

Cross-Team Collaboration

• Support the broader EMTM team in scaling data-driven product iteration across publications
• Translate data into clear, actionable insights for non-technical stakeholders

Job Requirements:

• 1–2 years of experience in a data analyst or similar role
• Strong proficiency in SQL, with hands-on experience in Athena and BigQuery
• Solid understanding of A/B testing methodology and statistical analysis
• Experience with data visualization tools (e.g., Looker, Tableau, Google Data Studio)
• Strong communication skills and ability to present findings clearly
• A collaborative mindset and willingness to learn

Engineering Manager

Job Type: Permanent
Location: Singapore, Hybrid Work Model
Salary: SGD 168,000 – 180,000 per annum + Insurance Benefits

We are seeking an experienced and hands-on Engineering Manager to lead a high-performing team delivering scalable, data-intensive applications. This role requires a strong balance of technical leadership, people management, and strategic thinking, with the ability to stay close to the code while driving engineering excellence.

You will play a key role in shaping architecture, improving engineering practices, and ensuring the successful delivery of high-quality software in a fast-paced, globally distributed environment. Collaboration across EU and US time zones will be required.

Key Responsibilities:

• Technical Leadership: Define architecture and platform strategy, drive best practices in scalability, performance, and reliability, and contribute hands-on to development and code reviews.
• Data & Platform Engineering: Design and optimize data models, pipelines, and analytical workloads across large-scale systems, ensuring high performance and maintainability.
• Stakeholder Management: Translate business needs into technical solutions, communicate trade-offs clearly, and coordinate delivery across global teams (EU & US time zones).
• People Leadership: Lead, mentor, and grow a high-performing engineering team, driving hiring, performance management, and a culture of ownership and continuous improvement.

Required Technical Skills & Experience:

Core Engineering:

• Strong experience with TypeScript across Back-End and Front-End development.
• Expertise in building and maintaining RESTful and/or GraphQL APIs.

Data Engineering & Databases:

• Hands-on experience with analytical/columnar databases (e.g., ClickHouse, BigQuery, Redshift, DuckDB).
• Strong proficiency in PostgreSQL and MS SQL Server, including performance tuning and query optimization.
• Experience designing and optimizing large-scale data processing systems.

DevOps & Infrastructure:

• Strong experience with Kubernetes (deployment, scaling, troubleshooting in production).
• Hands-on experience with Helm and containerized application deployment.
• Familiarity with cloud platforms (preferably Azure, but AWS/GCP also relevant).
• Experience building and maintaining CI/CD pipelines using GitHub Actions.

Preferred:

• Experience working with OMOP CDM (Observational Medical Outcomes Partnership Common Data Model), including data modelling, ETL pipelines, and schema design.
• Exposure to healthcare data standards (e.g., HL7 FHIR, ICD, SNOMED, LOINC) is a plus.
• Experience working with large-scale unstructured data or analytics platforms.
• Familiarity with modern Front-End frameworks and analytics-driven UI components.
• Background in data-intensive platforms, research, or real-world data applications.
• Contributions to open-source projects is a plus.

Job Type: Full-Time, 100% On-Site
Permanent Role

Role Overview:

We are seeking a highly analytical and detail-oriented Financial Consultant to serve as the financial subject matter expert within ERP implementation projects. This role is critical in ensuring that all financial processes and system configurations are aligned with both global and local accounting standards. You will act as the bridge between accounting principles and ERP system capabilities, translating complex financial requirements into scalable, compliant system workflows. As a key member of the project team, you will work closely with Lead Consultants, Functional Consultants, and stakeholders to design, validate, and optimise financial modules within ERP systems. This position is ideal for professionals who excel at the intersection of finance, systems, and process transformation, and who are passionate about driving financial accuracy through automation and system design.

Key Responsibilities

1. Financial Process Design & Implementation

• Design and configure ERP financial modules, including General Ledger, Accounts Payable, Accounts Receivable, Fixed Assets, and Cash Management.
• Develop scalable financial workflows aligned with IFRS and SFRS requirements.
• Ensure proper Chart of Accounts (COA) structure to support operational and reporting needs.

2. Regulatory & Accounting Compliance

• Ensure ERP configurations comply with applicable accounting standards, including IFRS and SFRS.
• Oversee system setups for taxation, revenue recognition, lease accounting, and asset capitalization.
• Stay updated on regulatory changes and assess their impact on ERP configurations.

3. Group Consolidation & Multi-Entity Structures

• Lead the design and implementation of group consolidation processes across multiple entities.
• Configure intercompany transactions, eliminations, and multi-currency handling.
• Ensure accurate and timely group-level financial reporting.

4. Cross-Functional Integration

• Collaborate with functional teams (Procurement, Sales, Inventory, Projects) to ensure accurate financial postings.
• Map operational transactions to correct General Ledger accounts and ensure end-to-end process integrity.
• Validate integration points between financial and non-financial modules.

5. Financial Reporting & Analytics

• Design and develop financial reports, dashboards, and management packs within the ERP system.
• Enable real-time financial visibility and actionable insights for stakeholders.
• Support audit requirements through structured and traceable reporting frameworks.

6. Data Validation, Support & Troubleshooting

• Identify and resolve financial discrepancies, reconciliation issues, and system imbalances.
• Support data migration activities, including validation of opening balances and historical data.
• Provide post-implementation support and continuous improvement recommendations.

Qualifications & Requirements

Minimum Requirements

• Bachelor's degree in Accounting, Finance, or a related discipline.
• Minimum 3 years of experience in ERP financial consulting or as a Systems Accountant / Finance Transformation professional.
• Strong working knowledge of IFRS and SFRS, with the ability to translate standards into system configurations.
• Proven experience in financial data analysis, reconciliation, and troubleshooting complex ledger issues.
• Strong analytical thinking, problem-solving, and stakeholder communication skills.

Preferred Qualifications

• Professional certification such as CA, CPA, or ACCA (active membership preferred).
• Experience in managing financial workstreams in full-cycle ERP implementations.
• Hands-on experience with group consolidation, intercompany eliminations, and multi-currency environments.
• Proficiency in financial reporting tools and advanced Microsoft Excel (e.g., pivot tables, data modelling).
• Familiarity with leading ERP platforms (e.g., Microsoft Dynamics 365, SAP, Oracle, NetSuite) is an advantage.

Job Opportunity: Permanent Role 100% On-Site from Monday to Friday

Role Overview:

The Project Coordinator plays a critical role in supporting the successful delivery of ERP implementation projects. Working closely with the Lead Functional Consultant, Project Managers, and clients, you will ensure that all project activities are well-coordinated, documented, and executed on schedule. This role focuses on maintaining operational efficiency across multiple workstreams managing timelines, tracking deliverables, and facilitating clear communication between stakeholders. It is ideal for a highly organized and detail-oriented individual who thrives in a fast-paced, structured project environment.

Key Responsibilities:
Project Coordination & Suppor

• Assist in the end-to-end coordination of ERP implementations, change requests, and support engagements
• Support project managers and consultants in ensuring smooth project execution

Schedule & Resource Tracking

• Maintain and update project plans, timelines, and resource allocations
• Proactively follow up with team members to ensure timely completion of tasks

Documentation & Reporting

• Prepare and distribute project status reports, meeting minutes, and action logs
• Maintain a centralized, accurate, and audit-ready project repository

Progress Monitoring & Risk Escalation

• Track project milestones, deliverables, and dependencies
• Identify potential risks, delays, or blockers and escalate them appropriately

Stakeholder Coordination

• Act as a coordination point between internal teams, clients, vendors, and subcontractors
• Organize and schedule meetings, workshops, and User Acceptance Testing (UAT) sessions

Administrative & Governance Support

• Manage project-related administrative tasks, including documentation and reporting
• Assist in tracking project progress against scope, timelines, and budgets
• Support preparation of internal and client-facing management reports

Key Requirements

• Diploma in Computer Engineering, Computer Science, Information Technology, or a related discipline
• 1-3 years of experience in project coordination, project administration, or IT support
• Basic understanding of ERP domains (e.g., Finance, Purchasing, Sales, Inventory)
• Proficiency in Microsoft Office applications, particularly Excel and PowerPoint
• Familiarity with project management or tracking tools (e.g., Jira, MS Project, Asana)
• Strong organizational and multitasking abilities with attention to detail
• Ability to work under pressure and manage competing priorities effectively

Preferred Qualifications

• Experience supporting ERP implementations (e.g., Epicor or SAP)
• Certification in project management (e.g., CAPM or equivalent)
• Ability to understand and translate technical concepts for business stakeholders
• Strong communication and interpersonal skills

Role Summary:

We are seeking a hands-on Data Engineer to spearhead our Databricks Proof of Concept (POC) on AWS. You will be responsible for the initial environment setup, security configuration, and designing the framework for our future data platform. Working across diverse AWS and external data sources, you will build a unified, production-ready Databricks environment that validates the platform for broader adoption.

Key Responsibilities:

Platform & Infrastructure Setup

• Configure Databricks workspace integration with AWS (S3, IAM, VPC).
• Design and implement a scalable Medallion Architecture using Delta Lake (Bronze / Silver /Gold layers).
• Build automated ingestion pipelines leveraging Databricks Autoloader.

Data Engineering

• Cleanse and transform raw data from S3, RDS, and APIs into Delta tables.
• Optimize Spark jobs for performance, reliability, and cost-efficiency.
• Connect diverse AWS and external data sources into a unified Databricks environment.

Governance &Evaluation

• Establish data governance standards using Unity Catalog. (Good to have — not a hard requirement for the POC.)
• Configure Databricks Clusters with Autoscaling and Spot Instances to manage AWS spend.
• Define and evaluate POC success metrics covering performance, cost, and ease of use.
• Set up an end-to-end pipeline (Source → S3 → Databricks → BI Tool) within agreed timelines.

Qualifications and Experience:

Must-Have Skills

• Databricks Mastery — Expert knowledge of Delta Lake and Medallion Architecture (Bronze /Silver / Gold).
• PySpark / Spark SQL — Ability to write and optimize Spark code; Python strongly preferred over Scala or R.
• AWS Infrastructure — Deep understanding of S3 (bucket policies, storage), IAM(roles and policies) for secure Databricks access.
• Data Ingestion —Hands-on experience with Databricks Autoloader or Unity Catalog for managed data governance.
• 3–5+ years of professional experience in Data Engineering with PySpark / SQL.

Good to Have

• Networking — VPC configuration and AWS networking concepts.
• AWS Glue or Amazon EMR experience.
• Databricks Certified Data Engineer Professional certification.
• Experience connecting OOTB BI tools to Databricks environments.

Role Summary:

We are seeking for a strategic Data Engineer focused on building and scaling enterprise data platforms and pipelines for an upcoming project. The position combines strong data engineering fundamentals with data strategy, architecture, and governance, while also driving AI-enabled innovation to improve decision-making and user outcomes.

It requires technical expertise, analytical thinking, and stakeholder collaboration across product, engineering, and business teams. The role also emphasizes a mindset of ownership, informed decision-making, and continuous learning to support evolving technologies and product growth.

Key Responsibilities:

This role spans end-to-end data engineering, AI, and platform delivery, focused on building scalable data systems that support product, analytics, and policy decisions.

You will design and maintain data pipelines, platforms, and models, deliver analytics and data products, and work closely with stakeholders to turn business needs into actionable insights. The role also includes developing and operationalising AI/ML and LLM-based solutions, supported by strong MLOps practices.

On the platform side, you’ll implement modern data architectures and DataOps practices (e.g., automation, streaming, data observability) to ensure high data quality, reliability, and performance, while managing technical debt.

You’ll also ensure governance, security, and compliance, proactively managing risks in data systems.

Beyond technical execution, the role requires ownership and leadership—driving projects independently, mentoring others, collaborating cross-functionally, and contributing to broader strategy, technology decisions, and organisational impact.

Requirements:

Experience & Education

• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline.
• At least 5 years of experience in data engineering.
• Proven experience delivering data platforms or products in large-scale, enterprise environments.

Technical Skills

• Strong expertise in data modelling (OLTP, OLAP, dimensional modelling).
• Experience with cloud data platforms and tools (e.g. AWS, Databricks, Redshift, Data Lakes).
• Proficiency in big data technologies (e.g. Hadoop, Spark, Kafka, Flink).
• Strong programming skills in Python, Scala, or Java.
• Experience with CI/CD and DataOps practices (e.g. SHIP-HATS or equivalent).
• Expertise in data integration techniques (e.g. ETL/ELT, streaming, APIs).

AI & Machine Learning (Advantageous)

• Understanding of machine learning and LLM concepts, including prompt engineering and AI application development.
• Familiarity with MLOps practices and cloud-based ML deployment.
• Awareness of responsible AI principles (fairness, robustness, safety).

Role Summary:

We are looking for a skilled Data Engineer to design, build, and maintain scalable, cloud-native data platforms. The ideal candidate has strong programming and SQL skills, hands-on experience with AWS, and a solid understanding of data modelling, ETL pipelines, and big data processing frameworks.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and data platforms.
• Build and optimize ETL/ELT workflows using PySpark, Pandas, and SQL.
• Work with large datasets using distributed processing frameworks such as Apache Spark.
• Design and implement data models to support analytics and reporting use cases.
• Develop and manage data solutions on AWS cloud platforms.
• Orchestrate data workflows using tools such as Apache Airflow.
• Collaborate with cross-functional teams to deliver reliable, secure, and high-quality data solutions.
• Implement best practices for data quality, performance, security, and governance.
• Support CI/CD pipelines and automate deployments using DevOps best practices.

Requirements:

• 3+ years of professional experience in Data Engineering or related roles.
• At least 2 years of hands-on experience with cloud-native data services.
• Strong proficiency in one programming language: Python, Java, or .NET.
• Advanced SQL skills with experience writing complex and optimized queries.
• Strong understanding of data modelling concepts (e.g., dimensional modeling).
• Experience with relational databases (PostgreSQL, MySQL).
• Experience with NoSQL databases (DynamoDB, CosmosDB) and data lakes.
• Hands-on experience with distributed data processing frameworks (Apache Spark / PySpark).
• Experience with workflow orchestration tools such as Airflow.
• Familiarity with CI/CD pipelines and Infrastructure as Code tools.
• Experience using Git, Docker, and Terraform is a plus.

Preferred Skills:

• Experience designing end-to-end data architectures in AWS.
• Strong understanding of system design, scalability, and security best practices.
• Good communication skills and ability to work in cross-functional teams.

Salesforce Developer

• Location: Singapore, Hybrid Work Model
• Job Type: 1-year Contract (Renewable)
• Salary Budget: 7-11K SGD Per Month

We are seeking an experienced Salesforce Developer to join a growing technology team supporting enterprise Salesforce implementations. This role is ideal for someone with strong hands-on development expertise across Salesforce Classic and Lightning, and proven delivery experience within Sales Cloud and Service Cloud environments.

You will work closely with business stakeholders, functional consultants, and technical teams to design, build, and enhance scalable Salesforce solutions that drive business impact.

Key Responsibilities:

• Design, develop, and implement Salesforce solutions across Salesforce Classic and Lightning Experience.
• Build and enhance functionality within Sales Cloud and Service Cloud, supporting end-to-end business processes.
• Develop custom solutions using Apex, Visualforce, SOQL/SOSL, Lightning Web Components (LWC), and Aura Components.
• Configure and maintain Salesforce features such as workflows, approval processes, validation rules, flows, and automation tools.
• Collaborate with functional teams to translate business requirements into technical specifications and deliverables.
• Develop and maintain integrations between Salesforce and external systems using REST/SOAP APIs and middleware tools where applicable.
• Support deployment activities, including sandbox management, release planning, and CI/CD processes.
• Ensure solutions follow Salesforce best practices around performance, scalability, security, and maintainability.
• Provide technical support, troubleshooting, and ongoing enhancements for production environments.
• Participate in code reviews, documentation, and mentoring of junior developers where needed.

Requirements:

• Minimum 4+ years of hands-on Salesforce development experience.
• Strong proficiency in both Salesforce Classic and Lightning Experience.
• Solid experience working on Sales Cloud and Service Cloud implementations.
• Familiarity with Salesforce security model, sharing rules, role hierarchy, and governance standards.
• Experience working in Agile project environments with cross-functional stakeholders.
• Strong communication and problem-solving skills.

Good to Have (Preferred Skills)

• Salesforce Platform Developer I (PD1) certification.
• Hands-on experience with OmniStudio, including: OmniScripts, FlexCards, DataRaptors, Decision Tables, Integration Procedures.
• OmniStudio Developer Certification is a strong advantage.
• Experience with DevOps tools such as Copado, Gearset, Jenkins, or Git-based CI/CD pipelines.

Job Summary:

We are looking for a senior hands-on AI/ML engineer to augment the team for the next 6 months.

• Build and scale production-grade full-stack GenAI solutions with a strong emphasis on backend systems, data, and AI/ML engineering.  
• Operate as a true partner to Business leaders - co-framing problems, influencing solution strategy, and co-owning measurable user and business outcomes - not as an execution-only engineering function.  

Job Responsibilities:

Product & Business Partnership  

• Co-own problem discovery with Product / Business: translate objectives into well defined, testable problem statements, user journeys, and technical hypotheses.  
• Challenge assumptions and requirements using user insights, data realities, feasibility constraints, and system impact; recommend alternatives when they better achieve outcomes.  
• Define and track success metrics (e.g., adoption, time saved, conversion, accuracy / quality, latency, reliability, cost-to-serve, risk reduction) and drive iteration when targets aren’t met.  
• Communicate clearly with executive, business, and engineering audiences - articulating trade-offs, decisions, and rationale.  

Solution Leadership

• Lead end-to-end solution for GenAI products: APIs, services, data pipelines, orchestration, LLM integration, retrieval, tool-calling, and UI/UX touchpoints as needed.  
• Make disciplined architectural trade-offs across performance, reliability, cost, extensibility, maintainability, and time-to-value.  
• Design for enterprise realities: identity / access, data residency, compliance constraints, multi-environment deployments, and integration with core systems.  
• Drive platform thinking: prioritize reusable components (libraries, templates, shared services) over one-off builds.  

Agentic & Full-Stack GenAI Applications

• Build and scale agentic GenAI applications that solve multi-step workflows on cloud platforms such as AWS and Azure.  
• Define and implement robust LLM patterns (prompting, RAG, tool orchestration, validation, and evaluation).  
• Implement LLMOps and lifecycle governance for models and prompts, including versioning, evaluation and monitoring.  
• Ensure solutions meet enterprise standards for quality, reliability, latency, and cost.  
• Embed Responsible AI, security, and compliance by design, partnering with Risk, Legal, and Security.  

Engineering Excellence & DevOps

• Provide hands-on leadership across the SDLC: design reviews, coding standards, testing strategy, code reviews, security reviews, and operational readiness.  
• Establish robust CI/CD and standardized environments for services and AI components utilizing cloud services.
• Ensure operational excellence through observability, incident management, reliability practices, and cost optimization.

Job Requirements:

• Proven track record in designing and building GenAI solutions, with a strong expertise in prompt engineering, LlamaIndex, Langchain, RAG, Agentic AI workflow,
• Knowledge graph, AI red teaming libraries, LLM monitoring and evaluation.  
• Over 7+ years of experience in the software development lifecycle as a developer, with a focus on writing production code.  
• Must have hands-on experience working with software development toolkits, and DevOps automation like Kubernetes, Airflow, Jenkins, Jira, Confluence and Git.  
• Excellent programming skills in Python and proficiency in PySpark.  
• Experience in Databricks, AWS bedrock, Microsoft Copilot Studio and Azure ML.  
• Strong leadership skill with ability to influence the thought process and drive alignment.  
• Excellent communication skills and a demonstrated ability to collaborate effectively with cross-functional teams.  
• Self-motivated and highly driven individual who can thrive in ambiguous requirements.

Job Summary:

We are seeking a highly skilled Big Data Platform Engineer to design, build, and operate large-scale, distributed data platforms. This role is responsible for ensuring the reliability, scalability, and performance of enterprise data systems, while driving automation, DevSecOps practices, and continuous improvement across data pipelines and platform infrastructure.

You will work closely with cross-functional teams to deliver robust, secure, and high-performing data solutions that support enterprise reporting, analytics, and data science initiatives.

Job Responsibilities:

• You are operating Global Data Platform components (VM Servers, Kubernetes, Kafka) and applications (Apache stack, Collibra, Dataiku and similar)
• Implement automation of infrastructure, security components, and Continuous Integration & Continuous Delivery for optimal execution of data pipelines(ETL/ELT)
• Develop solutions to build resiliency in data pipelines with platform health checks, monitoring, and alerting mechanisms, quality, timeliness, recency, and accuracy of data delivery are improved
• Apply DevSecOps & Agile approaches to deliver the holistic and integrated solution in iterative increments
• Liaison and collaborate with enterprise security, digital engineering, and cloud operations to gain consensus on architecture solution frameworks
• Review system issues, incidents, and alerts to identify root causes and continuously implement features to improve platform performance
• Be current on the latest industry developments and technology trends to effectively lead and design new features / capabilities

Job Requirements:

• 5+ years of experience in building or designing large-scale, fault-tolerant, distributed systems
• Migration experience of storage technologies (e.g. HDFS to S3 Object Storage)
• Integration of streaming and file-based data ingestion / consumption (Kafka, Control M, AWA)
• Experience in DevOps, data pipeline development, and automation using Jenkins and Octopus (optional: Ansible, Chef, XL Release, and XL Deploy)
• Experience predominately with on-prem Big Data architecture, cloud migration experience might come handy
• Hands-on experience in integrating Data Science Workbench platforms (e.g. Dataiku)
• Experience of agile project management and methods (e.g. Scrum, SAFe)
• Supporting all analytical value streams from enterprise reporting (e.g. Tableau) to data science (incl. ML Ops)
• Hands-on working knowledge of large data solutions (for example: data lakes, delta lakes, data meshes, data lakehouses, data platforms, data streaming solutions.)
• In-depth knowledge and experience in one of more large scale distributed technologies including but not limited to: Hadoop ecosystem, Kafka, Kubernetes, Spark
• Expert in Python and Java or another static language like Scala/R, Linux/Unix scripting, Jinja templates, puppet scripts, firewall config rules setup
• VM setup and scaling (pods), K8S scaling, managing Docker with Harbor, pushing images through CI/CD
• Experience using data formats such as Apache Parquet, ORC or Avro Experience in machine learning algorithms is a plus.
• Good knowledge of German is beneficial, excellent command of English is essential
• Knowledge of financial sector and its products

IT Cybersecurity Project Manager

Overview

Looking for a hands-on Cybersecurity Project Manager to drive key security and data protection initiatives across a large enterprise environment. This role blends project delivery, technical understanding, and stakeholder management.

Whats on offer: 

• Job Type: Contract role
• Location: Singapore

What You’ll Do

• Lead cybersecurity projects (DLP, SIEM, data classification, cloud security)
• Manage end-to-end delivery: timelines, risks, stakeholders, vendors
• Work closely with tech teams to implement and optimise security solutions
• Translate security/privacy requirements into practical implementations
• Drive data protection initiatives and support regulatory compliance
• Provide clear updates to leadership on progress and risks

What We’re Looking For

• 5–8 years in cybersecurity, infrastructure, or security project delivery
• Strong experience in DLP / SIEM / cloud security / IAM projects
• Solid understanding of security concepts, networks, and cloud (AWS preferred)
• Comfortable working with cross-functional teams and vendors
• Exposure to regulatory frameworks and data protection standards

Nice to Have

• PMP or equivalent
• AWS / Cloud Security certifications
• Security or privacy certifications

Job Summary:

We are seeking a Machine Learning Platform Engineer (MLOps) to bridge the gap between data science and production systems within our ML & AI platform team. The role spans the full ML lifecycle—from development to deployment—focusing on building robust data pipelines, managing model lifecycles, and enabling scalable AI integrations. You will also drive agentic workflows to support autonomous, AI-powered solutions in collaboration with cross-functional teams.

Job Responsibilities:

• Design, develop and deploy machine learning solutions and services
• Implement end-to-end machine learning pipelines from data ingestion to training and model serving
• Operationalize LLMs, embeddings, and multi-agent systems in real-world applications
• Manage the machine learning and model lifecycle (experimentation, registry, deployment)
• Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production
• Containerize applications using Docker and orchestrate them via Kubernetes
• Build and maintain CI/CD pipelines for ML models and LLM applications
• Collaborate with data scientists to refactor research code into production-ready Python code
• Monitor model performance, data drift, and performance in production
• Assess and integrate AI solutions ensuring optimal performance and reliability
• Design and implement production grade RAG systems
• Collaborate with infrastructure teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions

Job Requirements:

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
• Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code
• DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration
• Practical understanding of GPU architecture and cloud compute instances to optimize resource allocation for training and inference workloads
• MLOPS tools: hands on experience with MLflow (or similar tools like weights & biases) for experiment tracking and model registry
• Proven experience working with Large Language Models (LLMs)
• Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns
• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
• Hands-on experience with CI/CD pipelines (GitLab, Jenkins)
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
• Relevant work experience in machine learning, data science or a related field

Job Summary:
The candidate will be a member of the DT CLM ART - Asia team, which manages and delivers the business project portfolio to support the Bank’s growth strategy. Key features of the role and responsibilities include business analysis, requirements gathering, stake holder management, project management for smaller initiatives and change management. The Business Analyst works closely aligned with the Product Owner / Business stakeholders / Scrum Master or IT Project Leads and Developers to deliver projects end-to-end.

Job Responsibilities:

• Lead requirements gathering phase and deliver signed off Features
• Support preparation of business case and project planning
• Ensure all deliver available in signed off Features/EPIC are converted in respective user stories / Functional Document which can be understood by technical teams
• Ensure that all required deliverables are provided on-time and on-quality, in case of delay do timely escalations
• Issue regular & accurate status reports and institute progress meetings to keep stakeholders informed
• Ensure can play a QA role when role demand during SIT/UAT, before user coordination for sign off
• Change Management and Communications on requirements / functionality
• Manage interactions and communication with stakeholders
• Work with environment and deployment teams for timely production delivery (raise necessary set up activity)

Job Requirements:

• 8 to 15 years of experience in banking, preferably private banking and/or asset management
• Through understanding of private banking value chain with special focus on KYC and client onboarding related processes; key focus is on business understanding
• Good understanding of business processes, process design, and process re-engineering
• Good understanding of business project life cycle in addition to System Development Life Cycle
• Knowledge of SQL will be added advantage
• Knowledge of software quality process would be an advantage
• Knowledge of Agile methodology and experience of partnering with IT in Scrum model would be an advantage

Head of AI & Customer Experience (CX)

Overview

We are partnering with a global enterprise undergoing a significant digital and AI transformation. The organisation is investing heavily in building advanced AI capabilities to enhance customer engagement, drive commercial outcomes, and modernise digital experiences across multiple markets. This is a newly created leadership role responsible for defining and scaling AI-driven customer experience capabilities globally. The role sits within a central Data & Analytics function and works closely with senior leaders across commercial, digital, and technology teams.

Role Summary

The Head of AI & Customer Experience will lead the strategy, development, and deployment of AI solutions that directly impact customer-facing functions such as sales, marketing, service, and digital commerce. This individual will build and lead a high-performing team, establish best practices, and ensure AI initiatives deliver measurable business value at scale.

Key Responsibilities

Strategy & Leadership

• Define and drive the global AI strategy for customer experience
• Establish and lead an AI Centre of Excellence (CoE)
• Align AI initiatives with business priorities and commercial goals
• Act as a trusted advisor to senior stakeholders across business and technology

AI Product & Delivery

• Own the roadmap for AI-driven customer solutions, including:Personalisation and recommendation enginesGenerative AI and conversational interfacesCustomer analytics and insight platforms
• Lead cross-functional teams to design, build, and deploy AI products
• Ensure solutions are scalable, secure, and aligned with enterprise standards

Data & Technology

• Oversee the integration of AI solutions with enterprise data platforms
• Drive best practices in model lifecycle management and MLOps
• Ensure responsible and ethical use of AI technologies

Stakeholder & Ecosystem Management

• Partner with global business leaders across regions and functions
• Manage relationships with external vendors, partners, and technology providers
• Influence decision-making at senior leadership level

Team & Capability Building

• Build and lead a team of AI, data, and product professionals
• Foster a culture of innovation, experimentation, and continuous improvement
• Develop internal capabilities and promote knowledge sharing across the organisation

Experience

• Proven experience leading AI, data, or digital product teams in large, complex organisations
• Demonstrated track record of delivering AI solutions that drive business impact
• Experience building and scaling AI capabilities or platforms
• Strong background in customer-facing use cases such as personalisation, marketing, or digital experience
• Experience working in global or multi-regional environments

Technical & Functional Skills

• Strong understanding of modern AI technologies, including generative AI and machine learning
• Experience with cloud-based data and AI platforms
• Familiarity with product development methodologies and agile delivery
• Knowledge of data platforms, analytics, and AI deployment practices