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Data Engineer

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NTT DATA

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Location:
India , Bangalore

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Goldman Sachs is seeking a Data Engineer to join their datastore-migration Factory team. This role involves migrating data from on-prem DataLake to AWS LakeHouse, ensuring data integrity and optimizing consumption patterns. Candidates should have a Bachelor’s or Master’s degree in Computer Science or a related field, with 3-5 years of experience in a collaborative environment. Proficiency in Python, Kafka, and Snowflake is essential. The position requires strong stakeholder engagement and a rigorous approach to data validation. If you are ready to take on this high-visibility project, apply now!

Job Responsibility:

  • Perform end-to-end datastore migration from on-prem DataLake to AWS hosted LakeHouse
  • Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment
  • Executing the physical migration of underlying datasets while ensuring data integrity
  • Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements
  • Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg
  • Understanding usage patterns to deliver the required data products
  • Working with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows

Requirements:

  • Bachelor's or Master's degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field
  • Minimum of 3-5 years of professional hands-on-keyboard coding experience in a collaborative, team-based environment
  • Ability to troubleshoot (SQL) and basic scripting experience
  • Professional proficiency in Python or Java
  • Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience
  • Sophisticated understanding of Temporal Data Modeling (SCD Type 2)
  • Expertise in Schema Evolution (Iceberg Apache) and enforcement strategies
  • Advanced knowledge of data partitioning and clustering
  • Balancing Normalization vs. Denormalization and strategic use of Natural vs. Surrogate Keys
  • Candidates must demonstrate strong stakeholder engagement
  • Candidates must work with reconciliation frameworks
  • Ability to learn new workflows and language constructs

Additional Information:

Job Posted:
May 05, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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