Data Engineer - Python AND Kafka AND (Hadoop OR HDFS OR Hive) AND Snowflake AND apache AND (iceberg

Responsibilities: \n \nEngineer 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. This is a high visibility and crucial project for Goldman Sachs. \nResponsibilities of the Engineer includes: \n \nPipeline Migration \nLogic \u0026 Scheduling: Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment. \nData Transfer: Executing the physical migration of underlying datasets while ensuring data integrity. \nStakeholder 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. \n \nConsumption Pattern Migration \nCode Conversion: Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg. \nUsage analysis: Understand usage patterns to deliver the required data products. \nStakeholder 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. \n \nData Reconciliation \u0026 Quality \nA 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. \n \nEngineer 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. \n \nTechnical Skills: \n \nBasic Qualifications \nEducation: Bachelor\u2019s or Master\u2019s degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field. \nExperience: 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. \nLanguages: Professional proficiency in Python or Java. \nMethodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices \u0026 K8s deployment experience. \n \nCore Data Engineering Competencies: Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation: \nTemporal Data Modeling: Managing state changes over time (e.g., SCD Type 2). \nSchema Management: Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies. \nPerformance Optimization: Advanced knowledge of data partitioning and clustering. \nArchitectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys. \n \nTechnical Stack Requirements: \nWhile candidates are not expected to be experts in every tool, the collective team must cover the following technologies: \n \n\n\nExtraction \u0026 Logic \n \nKafka, ANSI SQL, FTP, Apache Spark\n\n \nData Formats \n \nJSON, Avro, Parquet\n\n \nPlatforms \n \nHadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQ \n \n \nCore Competencies: \n \nDemonstrates strong integrity and consistently models good conduct and ethical decision-making. \nActs as a trusted team player who collaborates effectively across multiple teams and functions. \nCommunicates with clarity and confidence - concise written updates, structured verbal briefings, and proactive stakeholder management. \nWorks effectively with global teams across time zones and cultures; builds alignment and resolves issues constructively. \nDelivery-focused with a strong sense of ownership; drives work to closure and meets commitments. \nBrings high energy and urgency to achieve targets while maintaining quality and professionalism. \nShows intellectual curiosity; asks thoughtful questions, surfaces risks early, and seeks feedback to continuously improve.\n