Total 1,217 data entry job vacancies in Information Technology category in Australia

About the Company

We are a premier global enterprise solutions and HR technology transformation partner working alongside hyper-scale multinational corporations, complex joint ventures, and global enterprise clusters. By combining advanced master data governance, predictive data modeling, and cutting-edge cloud architecture, we build secure and cohesive digital ecosystems that power intelligent HR operations. We focus on structural data integrity, cross-border data privacy engineering, and cultivating top-tier senior technical advisory talent in Singapore.

About the Job

We are seeking an experienced, elite-level SuccessFactors Data Lead to take complete strategic ownership of the end-to-end data strategy, architecture, and migration delivery across a complex multi-instance global enterprise. In this high-impact position, you will design the data models, master data governance rules, and quality thresholds across multiple SAP SuccessFactors instances, legacy platforms, and fragmented HR tools.

Your mission goes far beyond basic technical ETL (Extract, Transform, Load) execution. You must possess a deep functional command of how HR data behaves inside the SuccessFactors Employee Central engine. You will orchestrate complex multi-cycle data migrations, enforce regional data privacy standards (including GDPR and PDPA), and meticulously build a clean, trusted, and harmonized master data foundation engineered to support advanced human capital analytics and emerging GenAI/agentic frameworks.

Key Responsibilities

HR Data Strategy, Target-State Architecture & Harmonization

• Target-State Modeling: Define and own the enterprise HR data strategy across multiple SuccessFactors instances and legacy platforms, crafting target-state data schemas, position hierarchies, corporate taxonomies, and strict master data standards.

• Global Harmonization: Drive multi-instance data harmonization across global clusters, ensuring complete data consistency across Foundation Objects (business units, cost centers, job frameworks, pay structures), custom fields, and picklist values.

• Multi-Entity Calibration: Design a unified global master data framework that seamlessly accommodates regional legal entity nuances, joint venture structures, and cross-cluster reporting analytics frameworks.

End-to-End Data Migration & Cleansing

• Migration Orchestration: Blueprint, sequence, and execute large-scale data migration cycles (including initial profiling, mock data runs, differential delta mapping, reconciliation, and production cutovers) using specialized tools such as Spinifex, OpenText, or cloud ETL platforms.

• Data Integrity Gates: Formulate comprehensive mapping rules, structural transformation logic, automated validation scripts, and custom Excel data manipulation routines to bridge legacy data stores with SuccessFactors.

• Source-Level Remediation: Design and deploy automated data quality profiling and deduplication frameworks, establishing clear data health KPIs and collaborating with regional business teams to correct anomalies at the source.

• AI Readiness Hardening: Enforce strict data profiling thresholds to guarantee that processed employee records achieve the structural data maturity required for secure GenAI and agentic workflows.

Data Governance, Compliance & Integration Design

• Policy Enforcement: Establish and lead global data governance forums, defining clear data ownership boundaries, data steward accountabilities, centralized data dictionaries, and corporate business glossaries.

• Data Privacy Engineering: Define, configure, and audit strict localized data privacy controls, cross-border data transfer rules, and data masking protocols within SuccessFactors data models to ensure absolute compliance with GDPR and PDPA laws during testing and migration.

• Integration Data Contracts: Partner tightly with the Integration & Reporting Lead to define structural data contracts, API payload definitions, and master data synchronization paths between Employee Central and downstream systems (such as non-SAP HR payroll engines, corporate finance ledgers, and ITSM/ServiceNow configuration databases).

Team Leadership & Value Realization

• Workstream Leadership: Lead, mentor, and coordinate a cross-functional team of data analysts, migration developers, and data stewards across onshore (Singapore) and offshore execution hubs.

• Value Tracking: Establish value tracking metrics to measure data normalization successes, focusing on the reduction of manual reconciliation hours and the optimization of manager self-service data experiences.

Skills & Experience Required

Must-Have Skills (Mandatory for Skills Matching)

• SuccessFactors Data Mastery: Minimum 8+ years of hands-on HR technology experience with expert-level proficiency in HR data architecture, schema mapping, and master data management within the SAP SuccessFactors ecosystem.

• Employee Central Data Model Expertise: Deep functional, hands-on command of the SuccessFactors Employee Central (EC) data structure, including Foundation Objects, Position Management mechanics, and complex employment record schemas.

• Global Migration Lifecycle Execution: Proven experience leading the data track for massive, multi-instance global HR transformation programs, managing automated ETL cycles from legacy landscapes into SuccessFactors.

• Specialized HR Tooling: Practical experience with dedicated HR migration and profiling utilities (e.g., Spinifex, OpenText) or expert-level data manipulation scripting capabilities.

• Data Privacy & Compliance Governance: Demonstrable knowledge of implementing data privacy controls, access masking, and cross-border routing rules in compliance with GDPR and PDPA mandates.

Good-to-Have Skills (Preferred Differentiators)

• Official SAP SuccessFactors certification (Employee Central module preferred).

• Prior experience utilizing enterprise-grade master data management (MDM) platforms or automated data governance consoles.

• Familiarity with integration interface platforms (such as SAP Cloud Integration / CPI middleware) or downstream People Analytics reporting suites (Story Reports).

• Deep comprehension of data maturity indexing required to feed downstream Large Language Models (LLMs) or autonomous agent networks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Architecture, Information Systems Management, Business Analytics, or a related technical/quantitative discipline.

• Outstanding consultative, workshop facilitation, and stakeholder management skills, with a proven ability to align competing priorities across global corporate divisions.

How to Apply

Please click on the 'apply' button to apply online. For more information, please reach out to Vievien Nathan.

EA License Number: 94C3609

Key Responsibilities

• Build and maintain scalable data pipelines using Python
• Write production-grade Python code specifically for data processing, transformation, and ETL workflows
• Perform data cleaning, preprocessing, and feature preparation for analytics and AI use cases
• Use data analysis and manipulation tools to handle large datasets efficiently
• Develop reusable Python modules for data ingestion and pipeline automation
• Perform exploratory data analysis (EDA) to understand data patterns and quality issues
• Optimize data workflows for performance, scalability, and reliability
• Support data requirements for AI/ML and Generative AI systems
• Build data services and APIs to support downstream AI applications
• Ensure data quality, consistency, and observability across pipelines

Must have skills:

Python & Data Libraries (Hands-on Experience Mandatory)

Candidates must have solid practical experience with:

• Pandas — data manipulation, transformation, and analysis
• NumPy — numerical operations and array-based processing
• Matplotlib — data visualization and reporting
• scikit-learn — basic ML workflows and model evaluation
• PyTorch — deep learning and AI model experimentation

AI / Generative AI Enablement

• Prepare and structure datasets for ML and LLM-based systems
• Support integration of AI models into data pipelines and applications
• Enable workflows for Generative AI use cases (RAG systems, agent workflows)
• Work with multiple AI model providers:
• OpenAI
• Anthropic
• LLaMA
• Mistral
• Exposure to AI orchestration frameworks such as LangChain, AutoGen, and CrewAI

Core Requirements

• Solid hands-on Python coding expertise focused on data systems (critical requirement)
• Ability to write clean, efficient, production-grade Python code
• Thorough understanding of data structures, ETL pipelines, and data workflows
• Experience working with large-scale structured and unstructured data
• Solid SQL skills for data extraction and manipulation
• Understanding of data modeling and analytics workflows
• Ability to support end-to-end data-to-AI pipelines

Good to Have

• Experience with big data or distributed processing systems
• Understanding of vector databases and embedding-based retrieval systems
• Experience building APIs or services for data/AI systems
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Exposure to production monitoring and data observability tools

Role Overview

We are looking for an experienced Senior Data Engineer to build scalable, secure, and high-performing data solutions that support digital transformation and data-driven decision-making. In this role, you will design and maintain data pipelines, data models, and data warehouse solutions while working closely with business users, IT teams, and data stakeholders across complex technology environments.

Job Responsibilities

• Translate business data requirements into technical specifications.
• Collaborate with IT teams on technology stack, infrastructure, and security alignment.
• Design and build data ingestion pipelines to collect, clean, merge, and harmonize data from multiple source systems.
• Monitor databases and ETL systems, including capacity planning, maintenance, performance tuning, and issue prevention.
• Construct, test, and maintain reusable data models based on end-user requirements.
• Design and build secure mechanisms for users and systems to access data from the data warehouse.
• Research, propose, and develop new technologies and processes to improve data infrastructure.
• Work with data stewards to establish and enforce data governance policies, best practices, and procedures.
• Maintain data catalogue, metadata, and data lineage documentation.
• Implement data quality checks and validation processes to ensure data accuracy and consistency.
• Implement data security best practices, including access control, encryption, and data masking.

Job Requirements

• Bachelor’s Degree in Computer Science, Software Engineering, Information Technology, or related disciplines.
• Strong understanding of system design, data structures and algorithms, data modelling, data access, and data storage.
• Hands-on experience with cloud technologies such as AWS, Azure, or Google Cloud.
• Experience with Databricks.
• Experience in designing, building, and maintaining batch and real-time data pipelines.
• Experience with orchestration frameworks such as Airflow or Azure Data Factory.
• Proficient in Python, Shell Scripting, and SQL.

Preferred Requirements

• Familiarity with CI/CD pipelines.
• Familiarity with DevOps tools such as Docker, Git, and Terraform.
• Experience implementing technical processes for data security, data quality, and data governance.
• Familiarity with government systems and policies relating to data governance, data management, data infrastructure, and data security will be an advantage.
• Experience in Climate and Weather domains will be an added advantage.

At Intelligen, we’re building something different. Over the past three years, we’ve evolved from a bold startup into a trusted partner for some of Australia’s most complex data transformations. We’ve helped organisations move from legacy to modern cloud platforms, embed governance into decision-making, and bring AI into the hands of business users - responsibly and at speed.

Now, as we scale into Southeast Asia, we’re looking for a Data Engineer who’s passionate about modern, cloud-agnostic data platforms and building analytics-ready solutions on Snowflake. This is your chance to work on high-impact projects across the region and help shape how data is built, modelled, and used to drive meaningful outcomes.

About the Role

We’re seeking a hands-on Data Engineer with strong experience across cloud-agnostic data platforms, focusing on Snowflake, to design, build, and optimise data pipelines for clients across Southeast Asia and APAC.

You’ll be part of an integrated Intelligen consulting team, working closely with our architects, senior consultants, and client-side technical stakeholders. This role is ideal for engineers who are hands-on, delivery-driven, and comfortable working in fast-moving, iterative project environments.

What You’ll Do

• Design and build data pipelines across cloud environments (AWS, Azure, and/or GCP)
• Build and optimise data solutions in Snowflake
• Develop robust ETL/ELT solutions and data models to support enterprise analytics
• Optimise performance, scalability, and reliability across cloud data architectures
• Work closely with business stakeholders to translate needs into technical outcomes
• Contribute to data governance, quality, and lineage initiatives
• Collaborate with cross-functional teams across Australia and APAC
• Support pre-sales, technical design sessions, and proof-of-concept (POC) work

• 3–5+ years’ experience in data engineering roles
• Solid Snowflake experience is essential, including schema design, performance tuning, and warehousing best practices
• Strong, hands-on ETL expertise
• Ideally experience with SQL, data modelling (dimensional/domain), and modern data stack tooling.
• Ability to operate in “doer mode”, comfortable rolling up sleeves and delivering quickly in line with agreed standards
• Consulting experience is a plus but not required; strong communication and problem-solving skills are essential.
• Ability to deliver independently within a structured consulting engagement.

We’re not just delivering AI and data projects.. we’re humanising them. That means we care deeply about the how, not just the what. We value curiosity, creativity, and a willingness to challenge the status quo. We look for people who are driven to build a business, get curious, and offer opinions and ideas.

You’ll join a team that’s smart, kind, and ambitious. You’ll have real influence - in your projects, your practice, and the broader business. And as we grow, so will you.

Here’s what that looks like:

Grow With Purpose

• Structured development pathways so you always know what you’re working toward.
• Paid certifications across all major cloud and data technologies — because mastery matters
• Weekly training, guilds and knowledge exchanges where practitioners share real project insights.
  

Support That Helps You Thrive

• A dedicated support lead to mentor, guide and help you navigate your career
• Regular 360° feedback loops, giving you clear direction and honest insight into your progress.
  

A Community You’ll Enjoy Being Part Of

• Innovation days where you can experiment, prototype and sharpen new skills.
• Team days, social catchups,  many new community clubs…
• Opportunities to lead, influence and shape our growing practice as we expand across the region.
  

If you want to be part of a team that cares just as much about how we deliver as what we deliver; where curiosity is valued, ideas matter, and your impact is felt - drop us a message and start the conversation today...

Responsibilities

• Perform duty to manage data centre (DC) operations, maintenance, troubleshooting, project rollout and facilities related matters.
• Perform DC monitoring and maintenance on infrastructure systems, critical facilities and associated equipment.
• Perform preventive and corrective support to scheduled or unscheduled maintenance on DC infrastructure systems, critical facilities equipment and/or services.
• Ensure all subcontractors deliver a quality and competent service and all contractual obligations are met. Supervise the vendors to all scheduled and adhoc activities related to DC facilities.
• Perform DC and critical facilities work on environmental and management programs
• Perform equipment functionality test and data analysis
• Perform assets management duty, including maintaining of inventory, change and control programs and purchase of parts and supplies
• Promptly respond and attend to incident and/or emergency situations
• Provide standby support upon activation for shift duty stand-in and/or other coverage
• Conduct routine, sanity check and ongoing assessment of DC infrastructure systems and critical facilities operations

Requirements:

• Nitec / Higher Nitec / Diploma in Electrical/Mechanical/DC Infrastructure or relevant engineering discipline (Electrical, Mechanical or related fields)
• Additional certifications relevant to the industry is an added advantage
• 1 -2 years experience maintaining electrical, mechanical, fire protection system in facility management, particularly handling critical systems would be an added plus
• Strong problem-solving abilities, communication skills, and the ability to work independently and as part of a team
• Proficient in Computer skills eg. microsoft office, google emails, docs etc

5+ years of experience in data migration, data conversion, data quality, or data management projects.

• Experience supporting migration from legacy systems to modern enterprise applications, data platforms, or cloud-based solutions.

• Strong understanding of data profiling, source-to-target mapping, data cleansing, data transformation, reconciliation, and validation.

• Experience working with relational databases such as Microsoft SQL Server, PostgreSQL, Oracle, MySQL, or equivalent.

• Familiarity with ETL, ELT, or data processing tools such as Python, SSIS, Informatica, Talend, AWS Glue, or equivalent.

• Ability to work with technical teams to validate migration logic, transformation rules, migration jobs, and exception reports.

• Experience preparing clear migration documentation, data mapping specifications, cutover plans, validation reports, and reconciliation summaries.

• Strong analytical, problem-solving, and stakeholder management skills.

• Ability to communicate data issues clearly to both technical and non-technical stakeholders.

• Experience working in large-scale, secure, regulated, or public sector environments is advantageous.

Job Description:

• Responsible for the end-to-end ownership of Murex MX.3 Datamart reporting design, architecture, configuration, and delivery within a corporate banking transformation programme in Singapore.
• The role encompasses requirements analysis, datamart data model design, Datamart object configuration (dynamic tables, feeders, processing scripts, scanner templates), report development across Front Office, Back Office, Market Risk, Credit Risk, and Finance streams, and the strategic optimisation of batch report performance and EOD processing workflows.
• The incumbent will act as the primary Datamart workstream lead and Subject Matter Expert (SME), responsible for both hands-on technical delivery and the leadership of a team of Datamart reporting consultants and developers.
• The role requires deep expertise in MX.3 Datamart architecture, the Murex reporting engine, SQL optimisation, and capital markets reporting domains, combined with the team management and stakeholder engagement capabilities expected at a senior Lead level within a Tier 1 bank transformation programme.

Reporting Requirements & Architecture Design:

• Own and lead the Datamart reporting workstream for the MX.3 transformation programme, covering all user streams: Front Office (PnL, positions, trading blotters), Back Office (settlements, confirmations, nostro), Market Risk (VaR, stress testing, sensitivities), Credit Risk (PFE, CVA, CCR), and Finance (accruals, mark-to-market, P&L attribution).
• Engage directly with business stakeholders — including traders, risk managers, finance controllers, and operations heads — to gather, analyse, and formalise reporting requirements into detailed Business Requirement Specifications (BRS) and Technical Design Documents (TDDs).
• Understand the Murex system setup at the client: the organisation of support teams, EOD procedures, report delivery processes, and the interdependencies between Datamart and other MX.3 modules (FO, BO, Risk, Finance, Integration).
• Design a generic Datamart data model aligned to the bank's reporting taxonomy, then create the required Datamart objects (dynamic tables, feeders, extractions, scanner templates, processing scripts) to support all reporting use cases.
• Segregate and categorise reports by users, products, creation classes, fields required, complexity, and execution frequency to build a scalable and maintainable reporting catalogue.
• Communicate regularly with business Team Leads and programme stakeholders to ensure all Datamart deliverables are progressing as planned and expectations are actively managed.

Datamart Configuration, Development & Optimisation:

• Perform in-depth analysis of the Datamart setup and table structures to identify redundant objects, minimise batch execution time, and maximise reuse of existing Datamart components.
• Develop and configure all Murex Datamart objects: dynamic tables (PL, CS, DT, MV, LRB, PLVAR), feeders, batch of feeders, processing scripts, scanner templates, extractions, reporting tables, and pre/post filter conditions.
• Design and implement Simulation-based Reports and Risk Matrix-based reports for market risk and credit risk reporting consumers within the MX.3 platform.
• Configure and optimise EOD batch execution: implement parallel feeding strategies, resolve batch bottlenecks, tune query performance, and manage processing script sequencing within Control-M or equivalent job schedulers.
• Implement dataset historisation techniques within the Datamart to support time-series reporting, regulatory lookback requirements, and management information (MI) aggregation.
• Develop and maintain stored procedures, extractions, and complex SQL logic (Sybase/Oracle) for data processing, report population, and cross-module data joins leveraging the Murex FIN schema.
• Develop simulation views and scenario analysis reporting objects to support pre-trade and risk management reporting requirements for Front Office and Risk users.

Report Validation, Reconciliation & Quality Assurance:

• Execute processing scripts and batch jobs manually or via scheduling tools (Control-M), and reconcile Datamart report extraction output against onscreen MX.3 views and Mreport output to validate data accuracy.
• Analyse and resolve discrepancies arising from filter condition changes, feeder configuration differences, or data model modifications between Datamart report runs.
• Define and execute Datamart-specific test cases for SIT and UAT; ensure all test documentation and deliverables are consistent with programme testing standards and acceptance criteria.
• Assist in effort estimation for Datamart development and UAT scope; maintain accurate delivery tracking and escalate issues or risks to the Programme Manager in a timely manner.
• Participate in structured peer reviews of requirements, technical specifications, and testing documentation; provide constructive feedback and maintain quality standards across the Datamart workstream.

Migration, Integration & Market Data:

• Lead the migration of legacy Mreport-based reports to MX.3 Datamart equivalents, including gap analysis, mapping documentation, configuration build, and parallel run reconciliation.
• Manage market data integration and validation within the Datamart, ensuring rate curves, volatility surfaces, FX rates, and credit spread data are correctly sourced and represented in Datamart report calculations.
• Leverage NeoXam Data Hub scripting or equivalent data hub capabilities for data pipeline integration between MX.3 Datamart and downstream BI, regulatory reporting, or finance consolidation platforms.
• Coordinate with the Integration Lead to align Datamart extraction design with the broader enterprise data flow architecture, ensuring consistency of data lineage from trade booking through to report output.
• Configure MDCS (Market Data Curve Server), mxres configuration files, and launcher flags to support Datamart batch execution and reporting server performance requirements.

Team Leadership & General Management:

• Lead, manage, and mentor a team of Datamart reporting consultants and developers; delegate work effectively, review team output, and maintain delivery quality across all Datamart stream deliverables.
• Responsible for end-to-end ownership of Datamart reporting deliverables: from requirements intake through design, development, testing, UAT support, and post-deployment production validation.
• Ensure all team members are guided on best practices for Datamart configuration, object reuse strategies, batch optimisation, and coding standards within the MX.3 reporting framework.
• Demonstrate the ability to work proactively and independently where required, displaying strong initiative in identifying reporting gaps, performance issues, or data quality risks before they impact programme delivery.
• Contribute to programme governance forums by providing Datamart workstream status updates, risk and issue logs, and delivery milestone tracking to the Programme Manager and Steering Committee.

Requirements:

• 10+ years of hands-on experience as a Murex Datamart Developer, Consultant, or Reporting Lead on MX.3 programmes within corporate or investment banking environments.
• Mandatory in-depth expertise in MX.3 Datamart architecture and configuration: Datamart management, dynamic tables (PL, CS, DT, MV, LRB, PLVAR), feeders, batch of feeders, processing scripts, scanner templates, extractions, and reporting tables.
• Thorough understanding of MX reporting architecture, the MX.3 data model, the Murex FIN schema, and MXRes configuration files and launcher flags as they relate to Datamart reporting execution.
• Strong experience in Market Risk and Credit Risk report development within MX.3 Datamart, including Simulation-based Reports, Risk Matrix reports, VaR attribution, sensitivities, and PFE reporting.
• Proven experience with Mreport framework and Mreport to Datamart migration projects — including gap analysis, mapping, and parallel reconciliation — is highly desirable.
• Demonstrated track record of leading a Datamart reporting workstream or team across at least two full SDLC cycles within a capital markets platform implementation or upgrade programme.
• Good understanding of capital markets products and trade lifecycle across: FX (mandatory), Money Markets, Interest Rate Derivatives, Fixed Income, Equity Derivatives, and Credit Derivatives.
• Experience in NeoXam Data Hub scripting or equivalent data integration platforms for connecting MX.3 Datamart outputs to downstream systems is advantageous.
• Proven ability to gather, document, and validate complex reporting requirements from diverse business stakeholders (traders, risk managers, finance controllers, operations).

Education;

• Bachelor's degree or higher in Finance, Computer Science, Information Technology, Financial Engineering, or a related discipline.
• Formal Murex training or certification in Datamart and Reporting modules is advantageous. Master's degree in a quantitative or technical field is a plus.

Technical Skills:

• Excellent SQL programming skills (Sybase and Oracle); proficiency in PL/SQL for stored procedures, complex joins, and performance-optimised query design across the Murex FIN schema.
• Unix / Linux experience is necessary; Shell scripting (awk, sed, Perl, Bash) is highly desirable for batch automation, data processing, and monitoring script development.
• Python scripting for data processing, reconciliation automation, and Datamart batch management; experience with Python in NeoXam Data Hub or similar environments is advantageous.
• Experience with at least one reporting / BI tool: Actuate eRD Pro (preferred), Crystal Reports, MicroStrategy, or equivalent; Excel VBA for report automation and data validation is a plus.
• Familiarity with scheduling tools: Control-M (preferred), AutoSys, or equivalent for Datamart batch job management, dependency configuration, and execution monitoring.
• Desirable: knowledge of MRA/MRE or MLC module configuration; familiarity with Murex Pricing, Trade Repository, Trade Validation, MDCS, and MxML Exchange workflows.
• Java knowledge (especially Apache Camel, Maven) for integration touchpoints between Datamart and downstream systems is an advantage.

Purpose of the role – mission: The Data Scientist role is responsible for designing and managing universe studies, setting up the extrapolation for Retail Panels, documenting methodologies, ensuring quality assurance, and monitoring key performance indicators (KPIs) related to Panel Health. This role requires a strong background in data analysis, statistical modeling, and quality control processes as well as strong production system processes for PoS. This role supports the China market.  

Key activities:  

• Methodology and Universe Studies: Design and manage universe studies, including project management.  

• Document methodologies for transparency and provide clear explanations of existing methods.  

• Review results of universe studies and insert changes in the POS Manager.  

• Conduct impact analysis of universe studies.  

• Design and simulate extrapolation setups for new panels and sign off on the designs.  

• Quality Assurance: Optimize samples by analyzing shop contributions, detecting MDQC (Market Data Quality Check) outliers, meeting target sample requirements, and addressing issues like empty shops and slow sales.  

• Detect and address systematic methodological issues and prepare cleanup impacts for critical findings (end-to-end).  

• Modeling and Extrapolation: Model missing retailers completely outside the system and maintain complex models.  

• Support the setup of modeling missing retailers in the system and hand over to Stat Ops for ongoing maintenance and execution.  

• Implement new country-channel setups, including reviewing channel definitions, designing universes and samples, and providing setup instructions.  

• Quality Monitoring: Resolve Level 2 methodology clarification issues.  

• Monitor KPIs and conduct root cause analysis (RCA) for panel health, focusing on samples, missing retailers, universes, copy shops, and MDQC related to samples and extrapolation.  

• Define and specify improvement points for panel health.  

The Data Operations Analyst  is responsible of reformatting the retailer and vendor input files, validations, outlier checks and sending the deliverables to the next workstream in a correct and timely manner.  

• Be the contact for questionable sales and stores trend, leading the resolution in a client-focused and timely manner in cooperation with Input Validation, Retailer Vertical/ Retailer Engagement team and other downstream functions. To be able to identify, investigate and coordinate the resolution of data, process, or product related queries 
• Plan and execute complex daily personal workload and support to meet departmental and company schedules 
• Analyze and identify gaps and areas for improvement in reformatting and validations environment (CIP – Consumer Information platform) and drive convergence of processes and tools 

• Providing accurate and timely feedback to respective country teams, driving SOP and use of best-demonstrated practices 
• Working across relevant Operations/Enablement teams to ensure delivery to client expectations and satisfaction 
• Operate in a virtual/multi-cultural environment, liaising with stakeholders and colleagues