Data Platform Engineer

12500 Baltimore Avenue, Beltsville, MD 20705, USA

We are seeking a full‑time Data Platform Engineer to join our team in Beltsville, MD. This role owns the data systems that connect our production lines, QC, cell development, cycling labs, equipment logging, analytics, and internal applications. You will design, build, and operate the pipelines, databases, orchestration, monitoring, and back‑end services that move manufacturing and lab data into the dashboards, models, and tools our scientists, engineers, and operators rely on every day.

This is a hands‑on engineering role with broad scope – the right person is comfortable writing production code, maintaining existing systems, and partnering across data, IT/OT, and manufacturing teams, and using AI coding assistants and agentic tools as a force multiplier across the full development lifecycle. The role is open to mid‑level and senior candidates; we will level to fit.

Design, build, and maintain reliable data systems – orchestration, validation, monitoring, and alerting controls – for production, lab, and equipment data sources.

Own infra, schema design, ETL/ELT workflows, CI/CD, monitoring, and data governance.

Integrate with manufacturing and lab systems including ceramic production, cell manufacturing, QC, and robotic systems, and the internal applications built around them.

Build and maintain back‑end services and internal tools – VMs, APIs, data services, and lightweight web apps that surface data to engineering, ops, and executive stakeholders.

Design and operate the platform layer:
Docker/K8s, git, CI/CD, and backups. Identify incidents, drive to resolution, and lead post‑mortems.

Minimize single points of failure across the data stack through documentation, cross‑training, and engineering for maintainability.

Partner with Executive, IT/OT, R&D, and Operations stakeholders to scope work, plan deliveries, and roll out changes safely.

Employ governed AI workflows across day‑to‑day engineering, including code generation, refactoring, debugging, documentation, code review, and operational automation.

Maintain comprehensive documentation for systems, schemas, pipelines, runbooks, and backup/recovery procedures.

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent hands‑on experience in data engineering and backend systems.

4+ years of hands‑on experience building and operating production data systems, including database schema design (MS SQL/Postgres preferred), query/index tuning, and ETL/ELT workflows.

Strong knowledge for data engineering best practices – pipeline code, data validation, services, monitoring, and tooling.

Production experience with a pipeline orchestration platform (e.g. Airflow or Dagster).

Hands‑on experience with containerization, version control, and CI/CD workflows in a team setting.

Demonstrated ownership of operational monitoring, logging, alerting, and incident response for production systems.

Experience working with manufacturing, lab, sensor, or other equipment‑generated data – bridging the gap between raw machine output and analytics‑ready datasets.

Track record of maintaining and improving existing systems, not just building greenfield.

Hands‑on production use of AI coding assistants and/or agentic development tools with a clear point of view on where they help, where they don't, and how to use them responsibly.

Experience operating in hybrid environments that span on‑prem infrastructure and cloud services (Azure preferred) and thoughtful about where each system belongs.

Semantic models, dataflows, and downstream reporting infrastructure (Power BI preferred).

Internal application development experience – data entry UIs, sample/run trackers, equipment dashboards, or workflow apps tied to production systems.

Exposure to MES, ERP, SCADA (Ignition preferred), or other manufacturing‑traceability and production‑operations platforms.

Experience with regulated, quality‑sensitive, or audit‑driven data workflows (e.g., manufacturing, QC, automotive, aerospace, defense, life sciences).

Experience working in early‑stage environments where you owned systems…