We're looking for a Data Engineer to own the pipelines and warehouse at the core of that work. This is a hands-on role for an engineer who does excellent foundational work today and wants to grow with a platform that's still being built.
Core responsibilities- Design, build, and operate reliable pipelines that ingest from core business systems - CRM, ERP, through to operational and shop-floor data - into our data warehouse.
- Develop and optimize the warehouse across a structured, multi-layer architecture, with a focus on quality, performance, and trust in the data.
- Structure the warehouse and pipelines so the data is AI-ready - clean, well-governed foundations that AI systems and applications can reliably build on.
- Turn business questions from analysts and stakeholders into durable data models, not one-off extracts.
- Set the standards and practices for a data environment that's actively scaling.
- Move fluidly between hands-on engineering and higher-level design as the platform's scope grows.
RequirementsWhat we're looking for- Have at least two years building and operating production data pipelines and warehouses.
- Are strong in SQL and Python, with a track record of building and running production pipelines.
- Have hands-on experience with a modern cloud data warehouse or lakehouse (Microsoft Fabric, Snowflake, Databricks, BigQuery, or similar).
- Have a solid grasp of data modeling and warehouse design.
- Have worked with operational or industrial data, where the inputs are messy and reflect real-world systems.
- Take fragmented, multi-source data and turn it into a unified, trusted foundation others can build on.
- Are excited by where data engineering is heading beyond traditional analytics, and work AI-native - using modern AI tooling to move faster across the stack.
- Are comfortable operating with ambiguity and architecting where the requirements are still taking shape.
- Hold a bachelor's degree in computer science with a data engineering focus, or a related field.
Bonus points- Master's degree in a related field.
- Background in industrial engineering.
- Hands-on experience integrating ERP data as a source system.
- Exposure to asset-heavy or infrastructure-driven industries - manufacturing, energy, or power infrastructure.
- Interest in applied R&D and emerging data domains: sensor data, computer vision, or robotics.
- Familiarity with the data patterns behind AI applications - embeddings, retrieval (RAG), and chunking.
- Experience consolidating data across multiple business units or organizations.
BenefitsWhere you'll work & growBased in our Washington, DC-Baltimore area office on a hybrid schedule, working standard US business hours, with occasional travel to portfolio-company sites as projects require. In your first months, you'll stabilize and standardize the pipelines the rest of the team builds on. As the platform scales, your scope grows with it - from hands-on engineering into architecture and standard-setting. Raise the bar, and grow with it.
Compensation & benefitsCompetitive, commensurate with experience.
