Lead Data Engineer
Accenture (company site, opens in a new tab)6–8 yrsKochiOn-siteDirect career pageEst. 16–30 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain scalable, production-grade data pipelines and ETL/ELT workflows using Azure, Databricks, Python, Kedro, Apache Airflow, and related technologies.
- Develop and optimize backend automation including Azure Functions with Python and manage workflow orchestration with Apache Airflow (DAG creation, monitoring, troubleshooting).
- Collaborate closely with architects, UI developers, and data engineering teams to deliver reliable, high-performing data solutions and support production issues.
Minimum Requirements
- 5-8 years of professional experience in data engineering or related backend data processing roles.
- Proven hands-on experience with Azure, Databricks, Apache Airflow, Kedro, Python programming (including Pydantic models), and PostgreSQL SQL query optimization.
- Must have experience with Kafka for streaming data, Docker containerization, and GitHub version control including code reviews.
- Educational Qualification: Graduation (specific field not explicitly mentioned). Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in designing and supporting cloud-based distributed data platforms with strong expertise in Azure and Databricks ecosystems.
- Skilled in developing modular, maintainable, and production-ready data engineering code with an emphasis on workflow orchestration and automation.
- Comfortable working in cross-functional teams involving architects and developers, taking ownership of technical delivery and production support.