Data Platform Engineer: Build Self-Service Pipelines & SDKs

Coinbase, Inc.; Salt Lake City (UT); Hybrid; USD 186,000 - 219,000; Full time

Job summary

Coinbase, Inc. is seeking a Data Engineering Platform Engineer to join the Data Platform team. You will build abstractions, SDKs, and self-service apps that empower thousands of pipelines while ensuring data quality and security.

You will work closely with data analysts, scientists, and engineers to design scalable data models and robust data APIs, contributing across processing, storage, and tooling. A remote-first, hybrid setup supports quarterly in-person surges.

Qualifications

• 7+ years of experience in backend or data engineering.
• Strong Python or Java backend development skills.
• Fluent SQL for ETL/ELT, data quality, and analysis.
• Hands-on experience with Snowflake, Databricks, or similar.
• General experience working with data systems or data pipelines.
• Working knowledge of git, Linux, and Docker.
• Airflow, BI, and AI tool experience.

Responsibilities

• Build clean software abstractions and modular components to scale thousands of pipelines.
• Build and maintain data integration and processing SDKs for data teams.
• Design and build self-service applications for analysts and data scientists to manage pipelines.
• Build tooling for data security and observability: access controls, data quality, cataloging and lineage, auditing.
• Work cross-functionally with upstream/downstream teams to expose good data APIs and models.
• Convert requests from analysts, ML, and security into reusable scalable patterns.

Skills

Python

Java

SQL

ETL/ELT

Data pipelines

Git

Linux

Docker

Airflow

BI/AI tools

Tools

Snowflake

Databricks

Git

Linux

Docker

Airflow

Job description

Coinbase, Inc. is seeking a Data Engineering Platform Engineer to join the Data Platform team. You will build abstractions, SDKs, and self-service apps that empower thousands of pipelines while ensuring data quality and security.

You will work closely with data analysts, scientists, and engineers to design scalable data models and robust data APIs, contributing across processing, storage, and tooling. A remote-first, hybrid setup supports quarterly in-person surges.