Job Description:
• Design and implement the UniForm write layer with Delta and Iceberg dual metadata
• Build GCS to BigQuery ingestion pipelines for structured operational datasets
• Develop and implement solutions in Python and Spark
• Implement Kafka-based CDC patterns for real-time and near-real-time ingestion
• Develop data lineage, dependency tracking, and modular adapter code
• Configure Snowflake Horizon external tables for zero-copy reads
• Write data hub tables once using Delta Lake with Iceberg UniForm enabled for consumption by target platforms without conversion
• Implement and certify Delta Sharing endpoints for Databricks consumers
• Build governed access layer components including RBAC, connector registry entries, and tenant-scoped authorization
• Align semantic layer models with LookML and KPI catalog definitions
• Collaborate with cross-functional teams to deliver end-to-end features
• Troubleshoot issues across the full stack and contribute to code quality
• Design reusable data-sharing adapters connecting BigQuery-backed data products to Snowflake and Databricks
Requirements:
• 6+ years of proven enterprise-level experience in Python & Spark
• Advanced experience in GCP BigQuery
• Strong working knowledge of Apache Iceberg, Delta Lake, and Iceberg UniForm
• Experience with Delta Sharing and Kafka / CDC pipelines
• Specific work experience in Snowflake Horizon Catalog and Databricks Unity Catalog
• Solid experience with data lake architecture and ingestion pipeline design
• Excellent communication skills and ability to work cohesively with multiple teams
• Prior delivery in enterprise SaaS, media, or advertising technology (nice to have)
• Active daily use of AI-assisted development tools; Claude Code preferred (nice to have)
Benefits:
• Medical insurance
• Dental insurance
• Vision insurance
• Pet insurance
• Paid Time Off
• 401(k)
• Competitive compensation
• 100% remote work
• Full-time employment