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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:
Engineer will be part of the datastore-migration Factory team that will be responsible to perform for the end-to-end datastore migration from on-prem DataLake to AWS hosted LakeHouse
Pipeline Migration - Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment
Data Transfer - Executing the physical migration of underlying datasets while ensuring data integrity
Stakeholder Engagement - Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements
Consumption Pattern Migration - Code Conversion: Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg
Usage analysis: Understand usage patterns to deliver the required data products
Stakeholder Engagement - Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements
Data Reconciliation & Quality - A rigorous approach to data validation is required
Candidates must work with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows
Engineer will also need to work with our other internal data management platform, and must have an aptitude for learning new workflows and language constructs as necessary
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 trouble shoot (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
Demonstrated understanding of Temporal Data Modeling (e.g., SCD Type 2)
Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies
Advanced knowledge of data partitioning and clustering
Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys
Good conduct and ethical decision-making
Collaborates effectively across multiple teams and functions
Communicates with clarity and confidence - concise written updates, structured verbal briefings, and proactive stakeholder management
Works effectively with global teams across time zones and cultures
Delivery-focused with a strong sense of ownership
High energy and urgency to achieve targets
Intellectual curiosity
asks thoughtful questions, surfaces risks early, and seeks feedback