Lead Data Engineer

What you'll do

• Design and implement scalable, secure data platforms using Google Cloud managed services like BigQuery and Dataflow.
• Build reusable frameworks and tooling for data ingestion, transformation, quality, and orchestration across multiple teams.
• Develop shared transformation libraries in Python, SQL, and Beam for common patterns and data quality checks.
• Provide orchestration capabilities via Cloud Composer or Cloud Workflows using reusable DAGs and CI/CD integration.
• Implement robust data modeling, semantic layers, and security controls including IAM and row-level security.
• Enforce data quality, lineage, and observability using standardized metrics and monitoring dashboards.
• Optimize cost, performance, and reliability of GCP data workloads through partitioning, clustering, and autoscaling.
• Document patterns and best practices while providing enablement through workshops and code examples.

What we're looking for

• 5+ years of Database Engineering experience or equivalent demonstrated through work, training, military experience, or education.
• 5+ years of data management experience within a Public Cloud environment such as GCP, AWS, or Azure.
• 5+ years of hands-on experience with Python or Java, plus Spark SQL for building data pipelines and automation tooling.
• 5+ years of experience with orchestration tools like Cloud Composer/Airflow and CI/CD workflows.
• Experience with logging/monitoring stacks, automated testing, and data quality checks (preferred).
• Knowledge of cloud architecture principles including networking, security, IAM, reliability, and cost management (preferred).
• Experience with core GCP data services including BigQuery, Dataflow/Apache Beam, Dataproc, and Pub/Sub (preferred).
• Experience with Agile transformations, technology roadmaps, and working with onshore and offshore teams (preferred).