Senior Data Engineer (GCP • Python • Iceberg • Delta Lake • Kafka • Snowflake • Databricks)
About The Position
Railroad19, Inc is seeking a Senior Data Engineer with deep, hands-on experience in building modern lakehouse architectures on GCP. This role focuses on designing, developing in Python & Spark, and delivering reusable data-sharing adapters that connect BigQuery-backed data products to Snowflake and Databricks using Iceberg UniForm and Delta Sharing. About Railroad19: At Railroad19, Inc, we develop customized software solutions and provide software development services. We’re a specialized team of developers and architects. As such, we only bring an “A” team to the table, through hard work and a desire to lead the industry — this is our company culture — this is what sets Railroad19 apart. As a Railroad19 employee, you will be part of a company that values your work and gives you the tools you need to succeed. Our headquarters is in Saratoga Springs, New York, but this position is 100% remote. Railroad19 provides competitive compensation and excellent benefits, including Medical/Dental/Vision/Pet Insurance, Paid Time Off, and 401 (k). NO 1099, C2C, Corp-to-Corp; only full-time employment. NO Agencies.
Requirements
- 6+ years of proven enterprise-level experience in Python & Spark
- Advanced experience in GCP BigQuery
- Strong working knowledge of Apache Iceberg, Delta Lake, Iceberg UniForm
- Experience with Delta Sharing; Kafka / CDC pipelines
- Specific work experience in Snowflake Horizon Catalog; Databricks Unity Catalog
- Solid experience with Data lake architecture & ingestion pipeline design
- Excellent Communication skills and the ability to work cohesively with multiple teams.
Nice To Haves
- Prior delivery in enterprise SaaS, media, or advertising technology.
- Active daily use of AI-assisted development tools (Claude Code preferred).
Responsibilities
- Design and implement the UniForm write layer (Delta + Iceberg dual metadata).
- Build GCS → BigQuery ingestion pipelines for structured operational datasets.
- Develop and implement 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.
- All data hub tables are to be written once using Delta Lake with Iceberg UniForm enabled… readable by all target consumers without conversion.
- Implement and certify Delta Sharing endpoints for Databricks consumers.
- Build governed access layer components: RBAC, connector registry entries, 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.
Benefits
- Medical/Dental/Vision/Pet Insurance
- Paid Time Off
- 401 (k)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
