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Access | Information Management

Data Engineer

Posted 6 Days Ago
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In-Office
Industrial Estate, Mambalam Guindy, Chennai, Tamil Nadu, IND
Mid level
In-Office
Industrial Estate, Mambalam Guindy, Chennai, Tamil Nadu, IND
Mid level
Design, build, and maintain scalable ETL/ELT pipelines and data models using SQL and Python. Optimize database and pipeline performance, enforce data quality and governance, and collaborate with stakeholders to deliver analytics-ready datasets and data products.
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Job Summary & Responsibilities

We are seeking skilled Data Engineers to build, and maintain scalable platforms and pipelines that power analytics, reporting, and data products across the organization. You will develop robust ETL/ELT solutions, optimize data workflows, and enable trusted, high-quality data for business intelligence, advanced analytics, and data-driven decision-making. You will translate business requirements into robust database logic, automated data workflows, and insightful dashboards that enable data-driven decision-making across the organization. Depending on experience level, the role will contribute to solution design, development, optimization, and technical leadership within the data services team.

 

Roles and Responsibilities

  • Build, optimize, and manage data ingestion workflows from multiple structured and unstructured data sources.
  • Develop and optimize SQL queries, stored procedures, functions, and views for high-volume relational databases.
  • Design and maintain data models that support analytics, reporting, and data products.
  • Design, develop, and maintain scalable data pipelines using SQL, Python, and modern ETL/ELT frameworks.
  • Perform data profiling, cleansing, validation, and quality monitoring to ensure data accuracy, integrity, and consistency.
  • Optimize database and pipeline performance through indexing, partitioning, query tuning, and workload optimization.
  • Collaborate with Product Managers, and business stakeholders to understand business requirements and deliver analytics-ready data solutions.
  • Support the development and enhancement of data products by delivering reliable, scalable, and governed datasets.
  • Document data pipelines, data models, technical designs, and operational processes in accordance with data governance standards.
  • Implement best practices for data security, governance, metadata management, and compliance.
  • Contribute to automation, reusable frameworks, and continuous improvement initiatives.

Qualifications & Experience

  • Bachelor's degree in computer science, Information Technology, and Engineering.
  • 4--10+ years of strong hands-on experience in SQL development, ETL, and BI/reporting.

Required Skills & Experience

  • Strong proficiency in SQL (T-SQL / PL-SQL) with advanced query writing and performance tuning.
  • Hands-on experience with ETL/ELT tools such as SSIS, Azure Data Factory, Fivetran, AWS Glue
  • Experience with Azure Data Services, such as: Azure Data Factory, Azure Synapse Azure Data Lake Storage (ADLS), Azure SQL Database, Microsoft Fabric.
  • Hands-on experience with AWS Data Services including AWS Lambda, S3, Athena, Lake Formation & DataZone.
  • Strong programming skills in Python for data engineering and automation.
  • Strong data analysis skills, including data exploration, profiling, validation, KPI development, and translating business requirements into actionable insights.
  • Solid understanding of data warehousing concepts, star/snowflake schemas, and dimensional modeling.
  • Experience supporting or developing data products and understanding the end-to-end data product lifecycle.

Preferred Skills:

  • Familiarity with version control (Git) and CI/CD for data pipelines.
  • Exposure to Power BI, Service administration, gateways, and workspace management.
  • Understanding of data privacy, retention, and governance frameworks.

Competencies:

  • Strong communication and stakeholder management skills.
  • Ability to work both independently and collaboratively in a hybrid.
  • Attention to detail and commitment to data accuracy.
  • Adaptability and eagerness to learn new tools and technologies.

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