Data Engineer - Lakehouse Migration & Data Integrity

Apexon; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Goldman Sachs is seeking a data engineer to join the datastore-migration Factory team in Dallas. You will drive end-to-end migration from on-prem DataLake to AWS LakeHouse, refactor extraction logic, and migrate scheduling within the new environment.

You will handle data transfers, validate data with reconciliation frameworks, collaborate with data owners, and ensure artifacts meet business requirements while learning new workflows and languages as needed.

Qualifications

• Bachelor’s or Master’s in CS, Applied Math, Engineering, or related field.
• 3–5 years of hands-on coding in a team environment; able to troubleshoot SQL; basic scripting.
• Proficiency in Python or Java.
• Strong SDLC and CI/CD knowledge; Kubernetes deployment experience.

Responsibilities

• Refactor and migrate extraction logic and job scheduling from legacy frameworks to Lakehouse.
• Execute physical migration of datasets while maintaining data integrity.
• Engage with internal clients to hand off and sign off migrated assets.
• Translate legacy SQL/Spark consumption patterns for Snowflake and Iceberg.
• Validate migrated data against production flows using reconciliation frameworks.

Skills

Python

Java

SQL debugging

CI/CD

Kubernetes

SDLC

Data engineering

Education

Bachelor’s or Master’s in CS/Applied Math/Engineering

Tools

Snowflake

Apache Iceberg

Sybase IQ

Hadoop/HDFS/Hive

Job description

Goldman Sachs is seeking a data engineer to join the datastore-migration Factory team in Dallas. You will drive end-to-end migration from on-prem DataLake to AWS LakeHouse, refactor extraction logic, and migrate scheduling within the new environment.

You will handle data transfers, validate data with reconciliation frameworks, collaborate with data owners, and ensure artifacts meet business requirements while learning new workflows and languages as needed.