Data Engineer, Hardware Systems

Base Power Company • Austin, TX

43d

About The Position

We generate massive amounts of data from our hardware telemetry, lab equipment, field deployments, and distributed energy resource fleet. As a Data Engineer working with our Hardware team, you will design, build, and operate the core data infrastructure that turns raw hardware signals into actionable engineering insights.
You will own critical data pipelines and datasets that support product development, grid operations, reliability engineering, analytics, and business reporting. You'll work closely with hardware engineers, operators, business teams, and analytics to understand data needs and turn them into scalable, reliable systems. This is a hands-on role with real ownership. Your work will shape our data architecture as we grow and ensure it can scale with the company.

Requirements

• 5+ years of experience in data engineering, backend engineering with a strong data focus, or a hardware/systems role organizing and analyzing data to uncover root causes and trends.
• A strong background in building data infrastructure, with deep understanding of how to architect databases, data warehouses, and/or data lakes (e.g., BigQuery, Snowflake, Redshift, Databricks, or similar).
• Strong coding skills in Python, Go, SQL, and/or R, used for data manipulation, automation of ETL processes, and building custom visualization interfaces. Comfortable building and maintaining production data pipelines using modern data orchestration frameworks.
• Familiarity with hardware telemetry, time-series data, and sensor data from lab or field environments. Ability to look at disconnected log files and envision a structured system that makes that data actionable for a whole organization.
• Deep care about data quality, schema design, and building datasets that others can trust and understand using tools such as dbt.
• Familiarity with cloud infrastructure and infrastructure-as-code (e.g., AWS/GCP, Terraform).
• Enjoy working in fast-moving environments with evolving requirements and ambiguous problems. Take pride in building simple, reliable systems that solve real problems.

Responsibilities

• Diverse Data Integration: Design and manage the ingestion of disparate hardware datasets, including CAN telemetry, thermal chamber logs, power supply/grid sim/power analyzer readings, video feeds, and third-party systems, such that they can be synchronized for event-based analysis.
• System Architecture & Data Modeling: Build foundational data structures, schemas, and canonical datasets that store vast amounts of time-series hardware data in a way that remains searchable, performant, and scalable. Develop and own core data models used across the company for analytics, reporting, and decision-making.
• Pipeline Development & Operations: Design, build, and maintain reliable batch and streaming data pipelines with a focus on correctness, performance, and scalability. Automate ETL processes to move data from product, operational, and lab systems into our data platform.
• Visualization & Accessibility: Develop and maintain platforms that allow cross-functional teams to easily query, overlay, and visualize multi-modal hardware data to identify trends, anomalies, and test failures.
• Data Quality & Governance: Ensure "source of truth" datasets are consistent across lab environments and field deployments. Improve data quality, observability, and documentation so teams can confidently use data without deep context.
• Architecture Evolution: Help define and evolve our data architecture, tooling, and best practices as the company scales. Partner closely with EPD, operations, manufacturing, and business teams to understand data requirements and deliver practical solutions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed