Job description
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.
Core 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.
Skills/Experience:
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.
Preferred Experience – Nice to Have
Prior delivery in enterprise SaaS, media, or advertising technology.
Active daily use of AI-assisted development tools (Claude Code preferred).
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.