Total 868 data entry job vacancies in Information Technology category in Hong Kong

Summary

This role involves providing end-to-end content review and quality assurance services. The individual will be responsible for reviewing and annotating a wide range of content (e.g., text, images, videos) based on predefined guidelines. Additional responsibilities include grading assignments, ensuring consistency and fairness, and performing quality checks to maintain high standards. The role may also involve contributing to the development and refinement of guidelines, feedback loops, and continuous improvement initiatives.

Job Description

• Annotate content based on given standards and guidelines
• Grade assignments, projects, or assessments.
• Provide relevant data and prompt responses based on content.
• Provide feedback when discrepancies arise.
• Conduct research on various topics using reliable internet sources. 
• Conduct data collections based on client requirements. 
• Maintain detailed records for tracking and reporting.
• Collaborate to refine grading rubrics and annotation criteria. 
• Provide timely and accurate evaluation. 
• Gather information or data from various sources. 

About Centific 

Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.

Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.

Your Authentic Self at Centific 

Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, gender (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

What we do matters
Azendian Solutions, an AI, Data Science and Operations Technology company,develops solutions for energy and resource optimisation to achieve a smarter and more sustainable Built Environment by reducing carbon footprint, enhancing resource productivity and operations as well as lowering costs. Our AI-driven solution is game changing in its approach, leveraging on Machine Learning, Data Science, Cloud Computing with Operations Technology engineering systems.

The Role

The Data Scientist will implement cohesive data integration and analytics solutions involving both structured and unstructured data. Projects will include development of predictive, forecasting or operation research (optimisation) models as well as text mining and network analytics solutions.

Job Responsibilities

·      Work closely with clients and internal teams to understand business and operational challenges in smart building environments.

·      Lead or support client discussions to design, develop, and implement data-driven and AI-based solutions.

·      Translatereal-world problems (e.g., energy inefficiency, equipment faults) into data-driven and AI-based solutions.

·      Design and develop analytics and AI models for Anomaly detection, predictive maintenance, performance and energy optimization, etc

·      Work with real-world engineering and time-series data (e.g., equipment signals, environmental data, operational logs) including preprocessing of structured and unstructured data.

·      Develop and manage the end-to-end lifecycle of analytics projects, including problem definition and data scoping, feature engineering and modelling, deployment, monitoring, and continuous improvement.

·      Lead or contribute to small to mid-scale projects, taking ownership of delivery with appropriate guidance.

·       Proactively contribute to projects within your area of expertise and support cross-functional initiatives.

·       Define and enhance data collection processes to ensure relevant and high-quality data for analytics and AI systems.

·       Collaborate with data engineers and product teams across the full product lifecycle by concept and design, prototyping and testing, deployment and operationalisation.

·       Contribute to the development of AI-enabled features and products.

·      Present insights and recommendations clearly to both technical and non-technical stakeholders

Job Requirements

·               Bachelor’s Degree or equivalent in Computer Science, Mathematics, Statistics, Data Science, Engineering or related discipline. (Postgraduate qualifications in AI/ML are a plus but not required)

·               2–5 years of experience in data science, analytics, or applied machine-learning roles.

·               Strong foundation in the areas of programming languages (Python and SQL), data analysis and numerical computing (Pandas,NumPy/SciPy), machine-learning techniques (Scikit-learn, XGBoost or similar)

·               Strong knowledge in the areas of data science, programming languages (Python, SQL), machine learning and modelling technologies, statistical analysis, management, and strategic techniques.

·               Experience with data processing, feature engineering, and model development and working with real-world datasets (e.g.,time-series, IoT, operational data) is a plus.

·               Ability to Translate business or engineering problems into analytical and modeling approaches

·               Apply machine learning to practical use cases such as optimization, anomaly detection, or predictive analysis

·               Experience in Working with data models and writing efficient SQL queries

·               Familiar with Software engineering practices (e.g.,Git, basic CI/CD) is a plus

·               Familiar with Cloud platforms (e.g., AWS, Azure) is an advantage

·               Exposure to Smart building systems, HVAC, energy systems, or engineering domains is a strong advantage.

·               Strong problem-solving and analytical thinking skills

·               Excellent communication skills, with the ability to explain insights to non-technical stakeholders

·               Ability to work in a fast-paced environment and handle multiple projects

·               Willingness to learn and apply new technologies,including AI-assisted tools, to solve real-world problems

Job Summary

Support digitalisation initiatives by developing dashboards to improve visibility of operational risks and hazards. This role focuses on creating user-friendly data visualisation tools to enhance workplace safety and decision-making.

Job Responsibilities

• Design and develop dashboards to visualise risks and hazards across operational areas
• Gather and organise data to ensure accuracy and clarity in reporting
• Work with stakeholders to understand requirements and improve dashboard usability
• Maintain and update dashboards to reflect latest data and insights
• Support digitalisation and process improvement initiatives

Requirements

• Diploma in a relevant field (e.g. Engineering, IT, Data Analytics)
• Knowledge of dashboard tools such as Power BI, Power Apps, or similar platforms

All qualified applicants, please click “ APPLY NOW”

Or you may send in your resume to:

Whatsapp: https://wa.me/+6597430026  

Email : kimlow@recruitexpress.com.sg

Kimmy Low Yi Ting (Kim) | CEI Registration Number: R23112122

Recruit Express Pte Ltd Company Reg. No. 199601303W | EA LICENCE Number: 99C4599

Summary

This role involves providing end-to-end content review and quality assurance services. The individual will be responsible for reviewing and annotating a wide range of content (e.g., text, images, videos) based on predefined guidelines. Additional responsibilities include grading assignments, ensuring consistency and fairness, and performing quality checks to maintain high standards. The role may also involve contributing to the development and refinement of guidelines, feedback loops, and continuous improvement initiatives.

Job Description

• Annotate content based on given standards and guidelines
• Grade assignments, projects, or assessments.
• Provide relevant data and prompt responses based on content.
• Provide feedback when discrepancies arise.
• Conduct research on various topics using reliable internet sources. 
• Conduct data collections based on client requirements. 
• Maintain detailed records for tracking and reporting.
• Collaborate to refine grading rubrics and annotation criteria. 
• Provide timely and accurate evaluation. 
• Gather information or data from various sources. 

About Centific 

Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.

Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.

Your Authentic Self at Centific 

Centific is an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, citizenship status, age, mental or physical disability, medical condition, gender (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

KEY RESPONSIBILITY

• Assist in collaborating with end users to define their data needs and requirements for dashboard products.

• Coordinate with the external vendors to ensure the timely delivery of dashboard data products

• Monitor the usage & adoption rate and collect user feedback of all products

• Provide ongoing support and improvements to the dashboard data products based on user feedback and changing requirements.

• Any other general administrative duties/ad-hoc projects as assigned by immediate supervisor

REQUIREMENTS
• Degree in related fields
• Relevant working experience in building dashboard is a plus

Jessica Nguyen Huynh Thanh Truc

CEI Reg. No. R23113787

EA License No. 99C4599

We regret that only shortlisted candidates will be notified.

9pm to 6am

The Job:

• Perform pre-migration checks and testing to ensure service readiness, including:
• Inbound/outbound call scenarios
• Confirmation that subscriber data is fully synchronized prior migration

Interested applicants can send their detailed resumes to janelui@recruitexpress.com.sg or call JANE @ 6735 1955.

JANE LUI JIE'EN

CEI: R1104482

Company Reg. No. 199601303W || EA Licence No. 99C4599

About our group:

The AI and Tools Development team is at the forefront of AI Transformation within Seagate's Product Development Group. Our mission is to leverage AI technologies to accelerate product development, ensuring that we meet production volume and reliability standards. By utilizing AI, we enhance our research capabilities and drive continuous innovation.

About the role - you will:

• Join a dynamic data science team focused on using data to drive business growth and innovation.
• Work closely with senior data scientists to analyze data, develop models, and generate actionable insights.
• Contribute to solving complex, real‑world problems through data‑driven approaches and analytical thinking.
• Assist in the collection, cleaning, and preprocessing of large datasets from multiple internal and external sources.
• Conduct exploratory data analysis to uncover trends, patterns, and anomalies that inform business and engineering decisions.
• Develop and implement machine learning models and algorithms with guidance from senior data scientists.
• Collaborate with cross‑functional partners to understand problem statements and translate business needs into data‑driven solutions.
• Create clear data visualizations and reports to communicate insights to both technical and non‑technical stakeholders.
• Participate actively in team meetings, technical discussions, and continuous learning initiatives.

About you:

• Intrinsic motivation and strong attention to detail, with a commitment to delivering high‑quality, well‑reasoned work.
• A genuine passion for applying data science and analytics to solve meaningful and complex business problems.
• A growth‑oriented mindset, demonstrated through continuous learning, openness to feedback, and hands‑on skill development.
• Strong analytical and critical‑thinking abilities, with comfort navigating large, complex, and sometimes ambiguous datasets.
• Clear and effective communication skills, with the ability to convey complex technical concepts to both technical and non‑technical audiences.
• A collaborative and team‑oriented approach, contributing positively to a high‑trust, high‑performance environment.
• Proactive curiosity and self‑drive to stay current with emerging trends, tools, and techniques in data science, machine learning, and AI.

Your experience includes:

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related quantitative field.
• 0–2 years of hands‑on experience in data science, machine learning, or related areas (including internships or academic projects).
• Proficiency in programming languages such as Python or R.
• Foundational knowledge of machine learning frameworks and libraries (e.g., scikit‑learn, TensorFlow).
• Foundational understanding of core data science principles, including data analysis, modeling, and insight generation.
• Exposure to working with data to support decision‑making, business outcomes, or innovation initiatives.
• Experience collaborating with more senior team members in an analytical or technical environment.

Location:

The Shugart site (named after Seagate’s founder, Al Shugart) is a research and design center. Easily accessible from the One-North MRT Station, many employees choose to take mass transportation to work. Being a purpose-built building, The Shugart has excellent employee recreational facilities. Take an active break at our badminton courts, table tennis tables, in-house gym, and recreation rooms. Our yoga and Zumba classes are very popular. We also offer classes and interest groups in photography, gardening, and foreign languages, and have various on-site celebrations, and community volunteer opportunities.

Location: Shugart, Singapore
Travel: None

The Data Scientist works closely with business stakeholders to uncover challenges, refine use cases, and design analytical solutions that drive measurable outcomes. This role spans the entire data science lifecycle—problem framing, data preparation, modelling, evaluation, communication of insights, and enabling adoption through compellingvisualizations and decision‑support tools.

Key Responsibilities

1. Problem Definition & StakeholderEngagement

• Facilitate discussions with business users to understand their pain points, clarify objectives, and convert them into analytically sound data science problem statements.
• Collaborate with stakeholders throughout the project to refine hypotheses, validate findings, and align on priorities.
• Manage expectations and timelines while balancing analytical depth with business needs.

2. Data Preparation & FeatureEngineering

• Conduct data cleaning, preprocessing, and transformation for both structured and unstructured data to ensure high data quality.
• Perform feature engineering to extract meaningful attributes that enhance model performance.
• Identify relevant datasets and integrate multiple data sources to support analytical work.

3. Analytical Modelling &Experimentation

• Explore data using statistical techniques to uncover trends, patterns, and relationships.
• Build machine learning models for prediction, classification, clustering, or other analytical tasks as required by the use case.
• Evaluate model performance and iterate based on stakeholder feedback and performance metrics.

4. Insights Delivery & Communication

• Translate analytical results into actionable recommendations that stakeholders can apply to drive decisions or business improvements.
• Develop clear, compelling narratives that explain insights and model behaviours in an accessible manner.
• Present analysis with well‑designed visuals, dashboards, and interactive tools that support storytelling and data exploration.

5. Visualisation & User‑Facing Tools

• Design dashboards and interactive visualizations to facilitate self‑service analytics and real‑time data monitoring.
• Apply strong visualization principles to ensure insights are intuitive and impactful.
• Build and deploy customised visual interfaces tightly integrated with underlying data systems.

6. Deployment, Monitoring &Continuous Improvement

• Support model deployment into production environments and collaborate with engineering teams to operationalize models.
• Monitor model performance over time and recommend enhancements as required.
• Contribute to agile project workstreams and participate in ceremonies such as stand‑ups, reviews, and retrospectives.

Required Skills & Competencies

Analytical & Technical Skills

• Ability to convert business challenges into analytical questions and identify appropriate data sources.
• Proficiency in writing data preparation and analysis scripts using tools such as Python, R, SQL, pandas, or equivalent.
• Strong foundation in descriptive statistics, probability, data exploration, and hypothesis testing.
• Skilled in building and validating machine learning models, using modern techniques and frameworks.
• Solid understanding of system design concepts, data structures, and algorithms.

Data Visualization & Storytelling

• Strong command of data visualization principles and tools.
• Capable of developing dashboards and interactive visual tools (e.g., using Tableau, Power BI, Plotly, or custom frameworks).
• Ability to communicate analytical insights through structured storytelling tailored for decision‑makers.

Data Engineering Familiarity

• Understanding of data modelling, data access patterns, and data storage structures such as data lakes, data marts, and data warehouses.
• Familiarity with REST APIs, web protocols, and data extraction via web scraping technologies.
• Comfortable working with big data frameworks (e.g., Spark, Hadoop, Kafka) when required for large-scale processing.

Soft Skills

• Strong communication skills, both written and verbal, with the ability to influence non‑technical audiences.
• Effective stakeholder management and experience working in iterative cycles with feedback loops.
• Organized, self-driven, and able to manage multiple priorities in an agile environment.

Experience Requirements

• Proven experience conducting end‑to‑end data science projects—from scoping and data preparation to modelling and deployment.
• Experience collaborating with diverse teams and managing stakeholders across business and technical functions.
• Prior experience in agile project management or participating in agile delivery teams.

Qualifications

• Degree or equivalent experience in Data Science, Statistics, Computer Science, Engineering, Mathematics, Information Systems, or related fields.
• Experience with production‑grade machine learning workflows is an advantage.

Please send your details in MS Word format to john@oaktree.com.sg:

- Position applying for

- Current remuneration

- Expected remuneration

- Notice period

John Goh Meng Chye

EA License No : 06C4642

EA Reg No : R1102621

We regret that only shortlisted candidates will be notified.

Responsibilities:

• Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.

• Design and develop data products to support business decision making.
• Solve complex problems using analytical, statistical and machine learning approaches.
• Optimize data architectures such as data lakes, warehouses, and streaming systems to improve performance, scalability and platform stability.
• Collaborate with stakeholders to understand data requirements and translate them into technical solutions.
• Develop automated processes and frameworks to address recurring business questions.
• Ensure data governance, security and best practices are followed.

Requirements:

• Bachelor's degree or above in Statistics, Applied Mathematics, Computer Science or a related field.
• 2+ years of working experience in data engineering or a related role; Fresh graduates with relevant internship experiences are encouraged to apply.
• Strong proficiency in programming languages such as Java, Python and SQL.
• Hands-on experience in real-time data processing tools and streaming technologies (Spark, Flink, Kafka etc).
• Strong analytical and problem-solving skills.

Preferred:

• Basic understanding of machine learning concepts (e.g., classification, regression, clustering, neural networks etc).
• Familiarity with SQL and NoSQL databases.
• Experience building data products using cloud platforms and data warehousing solutions such as AWS and AliCloud.

The Data Engineer is responsible fordesigning, building, and maintaining data infrastructure that supportsanalytics, applications, and enterprise reporting needs. This includesconstructing scalable pipelines, managing data flows across systems, andenabling reliable storage, integration, and retrieval of information acrosscloud and on‑premise environments. The role involves close collaboration withcross‑functional teams to deliver data‑driven solutions that are robust, secure,and high-performing.

Key Responsibilities

1. Data Architecture & Development

• Design, create, and deploy data models, tables, views, and data marts across data warehouses, operational data stores, data lakes, and data virtualization environments.
• Build backend APIs and database structures to support applications and data products.

2. Data Extraction & Transformation

• Perform data extraction, cleansing, transformation, and blending across multiple sources.
• Conduct web scraping activities when needed, using appropriate automation tools.
• Ensure data reliability, accuracy, and consistency through well-structured data processing workflows.

3. Data Pipelines & Processing

• Develop and maintain large-scale batch and real-time data pipelines using modern data engineering frameworks.
• Implement ETL/ELT processes leveraging tools such as SSIS, AWS Glue, AWS DMS, Python, Lambda, ECS tasks, EventBridge, Spring, or similar technologies.
• Integrate data from distributed systems and eliminate data silos through scalable and secure data flows.

4. Collaboration & Product Delivery

• Partner with Project Managers, Data Architects, Business Analysts, Frontend Developers, Designers, and Data Analysts to deliver end-to-end data-driven solutions.
• Participate in Agile ceremonies and contribute to continuous integration and delivery practices.
• Engage in pair programming and participate in code reviews to ensure coding standards and quality.

5. Infrastructure, Cloud & Big Data

• Work with cloud platforms such as AWS, Azure, or Google Cloud to build and operate cloud-native data solutions.
• Design and manage data pipelines in big data environments using tools like Spark, Hadoop, Kafka, RabbitMQ, or similar technologies.
• Ensure systems are resilient, scalable, and suitable for production workloads.

6. Data Governance & Security

• Apply data governance principles, ensuring compliant access, secure storage, and proper data handling practices.
• Implement security best practices for data assets and support policy enforcement across systems.

Required Technical Skills

Data Processing & Programming

• Proficient in data cleaning and transformation using SQL, Python (pandas), R, or equivalent tools.
• Strong skills in ETL/ELT pipeline development and workflow orchestration.

Databases & Storage

• Hands-on experience designing and operating relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, MongoDB, Cassandra, Athena, SQLite, VoltDB, or S3-based storage.
• Familiarity with data warehouse, data lake, data mart, and data virtualization concepts.

System Design & APIs

• Solid understanding of system design, data structures, algorithms, and backend development.
• Comfortable working with REST APIs, HTTP protocols, and integrating various data sources.

Big Data & Distributed Systems

• Knowledge of distributed systems and tools (Hadoop, Spark, Kafka, etc.).
• Ability to implement streaming, micro‑batch, or batch processing pipelines.

Web Scraping & Automation

• Experience with web scraping technologies like BeautifulSoup, Selenium, CasperJS, PhantomJS, Node.js, or similar tools.

Security & Data Governance

• Familiar with access control, encryption, audit logging, and other data security practices.

Tools & Environment

• Comfortable working in both Windows and Linux environments.
• Experience using CI/CD pipelines and participating in DevOps-oriented workflows.

Soft Skills & Attributes

• Detail‑oriented with a strong focus on problem solving and analytical thinking.
• Good communication skills, capable of discussing technical topics with both technical and non‑technical stakeholders.
• Collaborative mindset and ability to work as a bridge between engineering and analytics teams.
• Self‑motivated, adaptable, and comfortable managing work in a fast-paced Agile environment.

Please submit resumes to john@oaktree.com.sg with the following details in MS Word format:

- Position applying for

- Current remuneration

- Expected remuneration

- Notice period

John Goh Meng Chye

EA License No : 06C4642

EA Reg No : R1102621

We regret that only shortlisted candidates will be notified.

Responsibilities:

• Lead and collaborate with data scientists and analysts to drive innovation, knowledge sharing, and continuous improvement.
• Design, develop, and deploy robust analytical and machine learning models using advanced statistical techniques.
• Partner with business and technical stakeholders to identify key challenges and translate them into data-driven solutions.
• Develop dashboards and data visualisations to effectively communicate insights to technical and non-technical audiences.
• Stay current with emerging data science trends, tools, and methodologies, applying relevant advancements where appropriate.
• Contribute to the establishment and enhancement of data governance, data quality, and analytics best practices.

Requirements

• Master’s degree or PhD in Data Science, Statistics, Machine Learning, Computer Science, or a related quantitative discipline.
• Significant hands-on experience in data science or advanced analytics roles, preferably within complex engineering or operational environments.
• Strong proficiency in Python and/or SQL, with experience using machine learning libraries and frameworks.
• Demonstrated ability to manage multiple projects concurrently and deliver high-quality outcomes in a fast-paced setting.
• Strong analytical and problem-solving skills, with the ability to interpret and extract insights from complex datasets.
• Excellent communication and stakeholder engagement skills, with the ability to explain technical concepts clearly to non-technical audiences.
• Familiarity with enterprise systems (e.g. PLM, MES, MRO) and cloud platforms such as AWS will be advantageous.

To submit your application, please apply online to apply@rn-care.com or call +(65) 6513 5697 for private and confidential discussion.

Your interest will be treated with the strictest of confidence. We regret that only shortlisted candidates will be notified or contacted.

RN Care Pte. Ltd
EA License No: 17C8900

Key Responsibilities

• Build and manage scalable big data platforms and pipelines (ETL/ELT)
• Implement automation and CI/CD for data and infrastructure
• Develop streaming and batch data solutions using Kafka & Spark
• Ensure platform reliability through monitoring and performance tuning
• Collaborate with cross-functional teams using Agile & DevSecOps practices

Mandatory Skills

• Hadoop, Spark, Kafka
• Strong experience in DevOps & CI/CD
• Experience with distributed systems and data pipelines
• Proficiency in Python / Java / Scala
• Linux/Unix environment experience
  
  Preferred Skills
• Kubernetes, Docker, Cloud (AWS/Azure/GCP)
• Data formats: Parquet, ORC, Avro

Tools: Ansible, Jenkins

Exposure to Dataiku / ML Ops is a plus

• Education
• Bachelor’s degree in Computer Science or related field

What you will be working on

The successful candidate shall be responsible, among others, to:

• Analyse, correlate, interpret and visualise data to uncover trends and patterns.
• Formulate and test threat hunting hypothesis.
• Produce insights and supporting evidence to support decision making.
• Compile and share intel with counterparts for prompt intervention actions.
• Translate concepts and results into reports and presentation for senior stakeholders

What we are looking for

• Background in Computer Science / Computer Engineering / Mathematics / Statistics / Data Science and Analytics or equivalent.
• Knowledge of cybersecurity concepts and applications. Candidates with relevant cybersecurity certifications are preferred.
• At least 3 year of experience in data transformation, interpretation, and quantitative data analysis.
• Knowledge of statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with their application is preferred.
• Experience in using databases and frameworks for big data analytics such as Hadoop / Hive / Spark, and able to write complex SQL queries.
• Domain knowledge and experience in Computer Networking, Network Security, or System Security is preferred.
• Fast learner with self-motivation and independence to acquire knowledge on new domains or technologies quickly.

About our group:

The Data Science and Tools Development team is at the forefront of AI Transformation within Seagate's Product Development Group. Our mission is to leverage AI and Machine Learning technologies to accelerate product development, ensuring that we meet production volume and reliability standards. By utilizing AI/ML, we enhance our research capabilities and drive continuous innovation.

We are seeking a highly skilled and versatile Full Stack Data Engineer to join our dynamic team. The ideal candidate will have a strong background in both data engineering and software development, with the ability to design, build, and maintain end-to-end data solutions. As a Full Stack Data Engineer, you will work closely with cross-functional teams to ensure seamless data integration, processing, and analysis, driving business growth and innovation.

About the role - you will:

• Design, develop, and maintain robust data pipelines to ensure efficient data flow and integration across various systems.
• Build and optimize data storage solutions, including data warehouses and data lakes.
• Develop and maintain APIs and microservices to support data access and integration.
• Implement data processing and transformation workflows using ETL tools and frameworks.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver actionable insights.
• Ensure data quality, integrity, and security through rigorous testing and validation processes.
• Monitor and troubleshoot data pipelines and systems to ensure optimal performance and reliability.
• Stay up-to-date with the latest advancements in data engineering, software development, and related technologies.

About you:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• 3+ years of experience in data engineering, software development, or a related field.

Your experience includes:

• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with SQL and NoSQL databases, including data modeling and query optimization.
• Familiarity with big data technologies such as Apache Hadoop, Spark, and Kafka.
• Knowledge of cloud platforms like AWS, Google Cloud Platform, or Azure.
• Experience with data integration tools (e.g., Apache NiFi, Talend) and ETL frameworks.
• Strong understanding of data architecture, data warehousing, and data governance principles.
• Excellent problem-solving skills and the ability to work collaboratively in a team environment.
• Strong communication and presentation skills, with the ability to convey complex concepts to diverse audiences.

Data engineer (Azure) – Synapse and Pyspark, Python, Datawarehouse and Azure Data Explorer, Azure Devops

Job Scope

• Design, review and development of Pyspark scripts. Testing, troubleshooting of data pipelines, orchestration.

• Designing and developing reports and dashboards in PowerBI,setting up access control with row level security DAX query experience.

• Establishing connections to source data systems such as on-prem databases, IOT devices, APIs.

• Managing the collected data in appropriate storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc. as required by the specific project requirements.

• Design, development of relevant data pipelines using pyspark, copy data activities for batch ingestion.

• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level as required by the analysis requirements of the project.

• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills & Experience

• Bachelor’s Degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, Pyspark or Big Data development.

• Sound Knowledge of Azure Synapse analytics for pipelines, orchestration, set up.

• 1-2 experience in Visualization design and development with Power BI. Knowledge on row-level security, access control.

• Sound experience in SQL, Datawarehouse, data marts, data ingestion with Pyspark and Python.

• Expertise in developing and maintaining ETL processing pipelines in cloud-based platforms such as AWS, Azure, etc. (Azure Synapse or data factory preferred)

• Team player with good interpersonal, communication, and problem-solving skills.

• Preferred to have Devops expertise.

Working hours :

8:30am to 6pm (Monday to Friday) onsite, no hybrid option.