Senior Data Platform Engineer — Remote

Prodege, LLC; California (MO); On-site; USD 185,000 - 220,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Flexible PTO

Paid holidays

Job summary

Prodege, a leading data-driven marketing and insights platform, seeks a Staff Data Engineer to own core data platform components and steer end-to-end data systems. You will lead from ingestion and modeling to governance and observability, delivering scalable, production-grade pipelines across a vast data footprint.

You will collaborate with cross-functional teams to accelerate BI, experimentation, and ML initiatives while upholding engineering standards and reliability.

Qualifications

• 5+ years of hands-on data engineering experience building large-scale data systems.
• Experience designing, deploying, and operating production-grade batch, ELT, and streaming pipelines.
• Strong understanding of modern data architecture, Medallion architecture, data contracts, schema evolution, and data modeling.

Responsibilities

• Architect, build, and operate high-capacity batch, ELT, event-driven, and near-real-time streaming data pipelines.
• Construct production-grade data platform components using Snowflake, dbt, Iceberg, Trino, Kafka, and related technologies.
• Design scalable data models following Medallion principles to support BI, analytics, and ML.
• Enforce data contracts, schema evolution, lineage tracking, governance, and observability.
• Collaborate with Engineering, Product, Analytics, BI, and ML teams to deliver trusted data foundations.

Skills

SQL

Python

Snowflake

dbt

Kafka

Iceberg

Trino

Kinesis

Tools

Kafka

Iceberg

Trino

dbt

Snowflake

Job description

Prodege, a leading data-driven marketing and insights platform, seeks a Staff Data Engineer to own core data platform components and steer end-to-end data systems. You will lead from ingestion and modeling to governance and observability, delivering scalable, production-grade pipelines across a vast data footprint.

You will collaborate with cross-functional teams to accelerate BI, experimentation, and ML initiatives while upholding engineering standards and reliability.