Title: Data Engineer 1 Enterprise AI is outpacing the infrastructure beneath it. Models improve every few months while the data feeding those models stays fragmented, duplicated, and undocumented. District builds forward deployed agents for forward deployed engineers, and those agents are only as good as the data pipelines underneath them. If you like turning messy source systems into clean, reliable data, are ready to work at petabyte scale, and want your work to power real agentic systems for real customers, we want to talk to you. The Role As a Data Engineer on District's Data Science/Engineering POD, you'll build the pipelines that move customer data from fragmented source systems into the clean, structured layers our AI solutions depend on. You'll partner closely with the AI Engineering POD, Product, and Customer Success as each new engagement brings its own data landscape. This is a hands-on, individual-contributor role for an engineer early in their career who has real production experience and is ready to work at petabyte scale. You'll own pipelines end to end, from ingestion through quality checks and monitoring, and your judgment will help inform how District's agent approaches customer solutions. You'll work directly with senior engineers and take on more ownership as you grow. Core Responsibilities Every customer engagement brings a different mix of databases, APIs, files, and legacy systems. Your job is to make that data usable, trustworthy, and cheap to query, at any scale. What You'll Do: • Build and maintain batch and incremental pipelines that ingest from customer source systems into District's data platform • Design ELT/ETL transformation layers that turn raw data into clean, well-modeled tables • Implement data quality checks at ingestion: row counts, null rates, key uniqueness, and schema validation • Make pipelines idempotent and re-runnable, with backfills that don't require code changes • Choose partitioning, clustering, and file-size strategies that keep queries fast and cheap as data grows • Instrument pipelines with volume, duration, cost, and error metrics, and set up alerting on drift • Review the pipelines District's agent produces and feed data engineering judgment back into how it makes decisions • Work with AI engineers to shape data for retrieval, context assembly, and fine-tuning datasets • Document data sources, lineage, and schemas so teammates and customers know what each table holds • Participate in code reviews and contribute to the team's data engineering standards and tooling What You'll Bring • 1–2 years of hands-on experience building data pipelines in a production environment • Strong SQL, including window functions, query plan inspection, and performance tuning on large tables • Experience with Spark or another distributed compute engine, including tuning shuffles and handling skew • Proficiency in Python for data processing and pipeline development • Hands-on experience with a modern cloud data platform or lakehouse • Experience with a workflow orchestration tool for scheduling and running pipelines • Experience with AWS, columnar storage formats, and big data concepts, with readiness to work at petabyte scale • Clear written and verbal communication, including the ability to explain why a pipeline design is right or wrong to technical and non-technical teammates • Self-motivated and able to work independently in a remote environment • A proactive attitude and willingness to learn new technologies and concepts Nice to Have: • Exposure to streaming or change data capture (CDC) patterns • Familiarity with how LLM and agent systems consume data: embeddings, retrieval, context windows, tool calls • Experience at a startup or on a customer-facing engineering team • Experience working with public sector data or compliance requirements Why Join District? This opportunity offers a unique opportunity to: • Join a fast-paced startup building agentic infrastructure that helps customers unlock and act on the data and systems they already have • Work on difficult data problems with real-world stakes across commercial and public sector customers • Grow your skills quickly alongside experienced data and AI engineers, with a clear path to more ownership • Enjoy the flexibility of a remote work environment and focus on results To Apply Please submit your resume and a brief cover letter outlining your interest in this role and any relevant experience you may have to [email protected] We're looking forward to hearing from you!