Senior Data Engineer
Merkle (a dentsu company) (company site, opens in a new tab)5+ yrsOn-siteDirect career pageEst. 14–24 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and deploy ETL/ELT data pipelines using Databricks (Spark SQL, PySpark) and SQL for data ingestion, transformation, and loading.
- Maintain and monitor data pipelines to ensure job execution within SLA timelines and resolve data quality issues.
- Collaborate with Engineers, Data Scientists, and Analytics teams to deliver data solutions and document code and operational processes.
Minimum Requirements
- Minimum 5 years professional experience in data engineering, ETL development, or similar analytics engineering roles.
- Strong expertise in Databricks (Spark SQL, PySpark) and SQL query optimization, joins, aggregations, and window functions.
- Hands-on experience with Python for data processing and scripting.
- Experience with cloud ETL platforms such as Azure Data Factory, AWS Glue, or equivalent.
Ideal Candidate Profile
- Experienced in building and supporting production-grade, cloud-native data pipelines prioritizing data quality and operational reliability.
- Proficient in collaborative agile environments working with cross-functional teams including Data Scientists and Analytics.
- Familiar with modern data engineering best practices including code reviews, documentation, and use of orchestration and version control tools (e.g., Apache Airflow, Git).