Senior Software Engineer, Data Platform

Block•Bay Area, CA, United States of America, CA

1d•$185,200 - $326,800•Remote

About The Position

We're hiring an experienced software engineer to build and own the data platform that helps teams across the company work with trusted data at scale. This role shapes the foundations for data warehousing, orchestration, business intelligence, governance, and Block's agentic workflows. You'll combine strong software engineering with hands-on experience working closely with data, building platforms that make it safer and faster for data practitioners to discover, produce, transform, govern, and use data.

Requirements

Senior-level software engineering experience, with strong Python skills and a record of designing, shipping, and operating production systems.
Hands-on experience building or operating data platforms, data products, or large-scale data infrastructure.
Experience with Snowflake, Databricks, or comparable modern data platforms.
Experience with Terraform and infrastructure-as-code practices.
A practical understanding of the tradeoffs involved in managing petabyte-scale data: performance, cost, reliability, access controls, lineage, quality, and governance.
Experience collaborating directly with data practitioners, and empathy for the workflows they use to turn data into decisions.
Strong technical judgment, clear communication, and the ability to lead across teams.

Responsibilities

Design, build, and operate core data-platform capabilities, including data warehousing, orchestration, business intelligence tooling, and data governance.
Build reliable Python services and developer-facing tools that improve how teams create and operate data products.
Develop scalable infrastructure as code with Terraform.
Establish patterns that let teams manage petabyte-scale data while maintaining strong governance, security, reliability, and usability.
Partner with data engineers, analysts, scientists, and product teams to turn their needs into durable platform capabilities.
Evaluate and build agentic workflows that make data work more effective, while maintaining appropriate controls and observability.
Set technical direction, raise engineering standards, and mentor other engineers.