Data Engineer

About Base Base is America’s next-generation power company. We’re rebuilding the foundation of modern civilization–electricity–by deploying a vast network of distributed batteries that is transforming today’s fragile, centralized grid into a resilient and abundant system. We are engineers, operators, and creatives solving some of the most complex, interdisciplinary challenges of our time. About the Role We process data from across the entire company: firmware telemetry from thousands of deployed batteries, ERCOT market signals, manufacturing test benches, lab equipment, and grid operations. As a Software Engineer on the Data Infrastructure team, you will design, build, and operate the backend data infrastructure that powers how we understand and run our business. This is a backend engineering role with a deep data focus. You won't just model schemas; you'll own the pipelines, systems, and platforms that move and transform data at every layer of the stack. You'll work closely with software engineers, hardware teams, markets, and operations to understand what data they need and build the systems that reliably deliver it. What you'll do Backend data systems: Build and maintain the core backend systems that ingest, transform, and serve data across the company -- from raw telemetry and operational events to clean, queryable datasets used in dashboards, models, and APIs. Pipel [... source excerpt omitted ...] rate reliable batch and streaming data pipelines with a focus on correctness, performance, and scalability. Own ETL processes end-to-end, from source system integration through to production delivery. Data modeling and architecture: Build foundational schemas and canonical datasets that store high-volume time-series and event data in a way that stays searchable, performant, and scalable. Own core data models used across the company for analytics, reporting, and decision-making. Diverse data integration: Manage ingestion across a wide range of data sources -- IoT telemetry, third-party APIs, operational systems, and internal services -- and build the infrastructure to synchronize [... source excerpt omitted ...] orthy. Improve observability so teams can use data with confidence. Architecture evolution: Help define and evolve our data architecture, tooling, and best practices as we scale. You'll have real input into how we build -- not just what we build. What you'll bring 5+ years in data engineering or backend engineering with a strong data focus Deep experience building data infrastructure -- data warehouses, data lakes, streaming systems, or similar (e.g., BigQuery, Snowflake, Redshift, Databricks) Strong coding skills in Python and SQL; experience with Go or another compiled language is a plus Comfortable building and maintaining production pipelines using modern orchestratio