Senior Data Engineer (GCP • Python • Iceberg • Delta Lake • Kafka • Snowflake • Databricks)
LocationU.S. Remote
Work moderemote
Typefull-time
DepartmentSoftware Engineering, Data Engineering Team
Company size1+ people
First seen1mo ago
Last seen1d ago
About the role
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:
About the company
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:
Responsibilities
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Design and implement the UniForm write layer (Delta + Iceberg dual metadata).
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Build GCS → BigQuery ingestion pipelines for structured operational datasets.
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Develop and implement in Python and Spark.
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Implement Kafka-based CDC patterns for real-time and near-real-time ingestion.
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Develop data lineage, dependency tracking, and modular adapter code.
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Configure Snowflake Horizon external tables for zero-copy reads.
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All data hub tables are to be written once using Delta Lake with Iceberg UniForm enabled… readable by all target consumers without conversion.
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Implement and certify Delta Sharing endpoints for Databricks consumers.