Responsibilities:
• Design and build scalable data pipelines to ingest, process, and transform
structured, semi-structured, and unstructured data from heterogeneous sources.
• Develop batch and streaming pipelines using Pub/Sub, Dataflow, Cloud Run,
and Cloud Functions for real-time and near-real-time processing.
• Implement data models and optimize performance for OLTP and OLAP sinks,
including Cloud Spanner, BigQuery, and relational stores.
• Participate in mainframe modernization initiatives, extracting,
transforming, and migrating legacy datasets into GCP-native platforms.
• Ensure data quality, lineage, and governance practices using GCP-native
tools.
• Collaborate with business and application teams to deliver end-to-end data
solutions.
Requirements:
• Strong experience with GCP services: Pub/Sub, Dataflow, Cloud Run, Cloud
Spanner, BigQuery.
• Hands-on with Python/Java/Scala for data engineering pipelines.
• Good knowledge of mainframe data formats (COBOL copybooks, VSAM, DB2) and
integration with modern platforms.
• Solid understanding of OLTP vs OLAP workloads and best practices for
optimization.
• Familiarity with DevOps practices for CI/CD on GCP.
Information
Locations Position Open to Anywhere in the US, but will work on-siteIndustry Information TechnologyStatus OpenJob Age 32 Day'sCreated Date 09/03/2025No.of Positions 2Duration 12 MonthsZip Code
