Back
Strong brand, metro locations, and a common mid-level data engineer profile increase competition.
Data engineering skills are transferable, but Lakehouse migration and Snowflake/Iceberg expertise raise domain specificity.
Mandatory 6+ years plus specific AWS, Spark, and Lakehouse migration skills enforce strict technical shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead end-to-end migration of data pipelines from on-prem Data Lake to AWS-hosted Lakehouse architecture (Snowflake and Iceberg).
Develop, refactor, and optimize data ingestion pipelines ensuring data integrity, reconciliation, and quality validation.
Engage with internal stakeholders and collaborate with platform and data management teams for migration validation and adoption of new workflows.
6+ years of hands-on development experience in data engineering.
Mandatory experience with AWS Cloud and on-prem to Lakehouse migration.
Proficiency in SQL, Python, Spark, and knowledge of data engineering concepts like SCDs, data lineage, schema evolution.
Work model requires hybrid onsite presence 3 days/week in Bengaluru or Hyderabad.
Experienced in building and optimizing scalable data ingestion pipelines and migrating complex data architectures.
Skilled in stakeholder management and capable of working effectively with global, cross-functional teams.
Technically strong with practical knowledge of data engineering best practices, CI/CD, and data platform tools like Snowflake and Apache Iceberg.