Sr GCP Data Engineers / Architects

We are seeking a Senior GCP Data Engineer / Architect to design and implement scalable cloud data platforms and data pipelines on Google Cloud Platform (GCP). This is a senior, hands-on engineering role for someone who can lead technical architecture while also developing, reviewing, and supporting production code.

The engineer will design GCP data and lakehouse architectures, develop batch and distributed data pipelines, and build solutions using BigQuery, Dataflow/Apache Beam, Dataproc/Spark, and Python. The individual will work directly with technical teams and customers to translate requirements into scalable GCP data solutions.

This is not purely an architecture role. The engineer must be comfortable writing Python, reviewing code in GitHub, troubleshooting implementations, and contributing directly to delivery.

The role is primarily remote but requires the ability to travel to the Reston, VA/customer location periodically. On-site requirements may range from several days to approximately 1-2 weeks in a month depending on customer needs.

• Senior-level hands-on GCP data engineering and/or data architecture experience
• Strong BigQuery architecture and implementation experience
• Hands-on Dataflow and/or Apache Beam
• Hands-on Dataproc, Apache Spark, and/or PySpark
• Strong Python development experience
• Experience designing and implementing production data pipelines
• Experience designing scalable GCP data platforms and/or lakehouse architectures
• Ability to write, review, troubleshoot, and deploy production code using GitHub-based development workflows
• Ability to operate at Senior Engineer / Architect level and participate in customer-facing technical discussions
• Cloud Composer / Apache Airflow
• Pub/Sub
• dbt
• PostgreSQL, Cloud SQL, AlloyDB, Oracle, or other relational/distributed databases
• Database migration and performance optimization experience
• GCP Professional Data Engineer certification
• GCP Professional Cloud Architect certification
• Experience supporting federal/public-sector or highly regulated environments
• Experience with secure or classified cloud environments
• Active security clearance
• Experience building data pipelines that support downstream ML/AI applications
• MLOps, Vertex AI, Gemini, or other Google AI/ML exposure