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Tier-1 brand, Bangalore metro, common Data Engineer title, and broad cloud/tech requirements increase applicant competition.
Core data engineering skills are transferable, but governance, MDM and finance domain preferences moderately reduce portability.
Explicit 8+ years and mandatory cloud/data platform expertise increase shortlisting rigidity.
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Design, develop, and support end-to-end data pipelines using cloud platforms like AWS, Redshift, Databricks, and Snowflake.
Build scalable data ingestion, transformation, and validation frameworks with Python, SQL, and Shell scripting, ensuring performance and data quality.
Collaborate with architects and application teams on data strategies, perform pipeline optimization, and maintain production stability including on-call and incident management.
Minimum 8+ years of experience in data engineering, ETL, data ingestion, data warehousing, and analytics.
Proficiency with cloud data platforms such as AWS (including AWS S3, Amazon Redshift), Databricks, Snowflake.
Strong skills in Python, SQL, Shell scripting, and experience with data pipeline architecture and operational support.
Experience with tools like GIT, Harness, JFrog, CI/CD pipelines, and project management tools like JIRA.
Experienced in designing and optimizing data warehouse solutions with modern cloud technologies and frameworks (Iceberg, MDM, Data Quality).
Skilled in implementing automated data validation, quality rules, and governance for trusted analytics datasets.
Comfortable working in Agile environments, participating in architecture discussions, and collaborating across teams to deliver technical solutions aligned with business requirements.