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Tier-1 brand, popular senior data engineer role with broad stack and metro context increases competition.
Technical data engineering skills transfer well, but financial governance and MDM increase domain sensitivity.
Explicit 8+ years and many mandatory cloud, data, and governance skills make shortlisting strict.
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Design, develop, and support end-to-end scalable data pipelines and ETL processes on cloud platforms including AWS, Redshift, Databricks, and Snowflake.
Optimize data ingestion, transformation, and validation frameworks using Python, SQL, Shell scripting, Spark, and Informatica ETL for analytics-ready datasets.
Collaborate on architecture design, implement data quality frameworks, ensure compliance with data governance and security, and support production stability including incident management.
8+ years of experience in data engineering, ETL, data ingestion, data warehousing, and analytics.
Hands-on experience with cloud data platforms: AWS, Redshift, Snowflake, Databricks.
Proficient in Python, SQL, Shell scripting, Spark, and Informatica ETL.
Experience with data quality frameworks, CI/CD tools (GIT, Harness, JFrog), and Agile delivery practices (JIRA).
Experienced in building and operating both batch and streaming data pipelines with a strong focus on performance and reliability on cloud platforms.
Skilled in designing logical/physical data models and implementing automated data validation, quality rules, and lineage capture to ensure trustworthy data.
Capable of collaborating across architects, application teams, and business stakeholders to translate requirements into scalable technical solutions while supporting production operations.