Forward Deployed Engineer, Data

Why this role matters

First Resonance builds the ION Factory OS — the operating system powering next-generation manufacturing for companies building rockets, satellites, eVTOLs, clean energy systems, robotics, and autonomous vehicles.

Our customers generate critical data across ION, ERP, PLM, quality, finance, procurement, equipment, and homegrown systems. That data only creates value when it is trustworthy, connected, and available at the moment a factory team needs to make a decision. We are hiring a Forward Deployed Engineer, Data to turn fragmented manufacturing data into durable, production-grade data products and pipelines.

This is a hands-on, customer-facing engineering role. You will work directly with customer data, manufacturing, and IT teams and partner closely with Forward Deployed Engineering, Product, and Engineering. You will move from an ambiguous operational question to a deployed solution — designing the architecture, writing production code, validating the data, launching with users, and keeping it reliable.

What you’ll own

• Deliver customer data solutions end to end: Lead discovery, requirements, architecture, implementation, testing, go-live, documentation, and operational handoff for high-value customer use cases.
• Build reliable data pipelines: Ingest, transform, reconcile, and serve data across ION and customer systems using APIs, webhooks, event streams, batch workflows, and modern data tooling.
• Model complex manufacturing operations: Translate parts, bills of materials, work orders, inventory, quality, labor, costs, and engineering changes into clear and maintainable data models.
• Make data trustworthy: Establish validation, observability, lineage, access controls, retry and backfill patterns, and incident-response practices so customers can depend on production data.
• Turn deployments into product leverage: Convert successful customer work into reusable pipelines, semantic models, reference architectures, test harnesses, runbooks, and platform improvements.
• Lead through ambiguity: Set expectations with technical and nontechnical stakeholders, surface risks early, make practical tradeoffs, and remain accountable for the customer outcome.

What we’re looking for

• 5+ years of experience in data engineering, software engineering, analytics engineering, or another role building production data systems.
• Strong programming ability in Python and fluency with SQL, data modeling, and software-engineering practices such as testing, version control, and code review.
• Experience building and operating data pipelines across APIs, transactional databases, event streams, object storage, and cloud data platforms.
• Sound judgment around distributed-system and data-quality failure modes, including idempotency, ordering, schema evolution, reconciliation, observability, and access control.
• Ability to work directly with customers, turn ambiguous operational problems into clear technical plans, and communicate tradeoffs to both engineers and business leaders.

If you do four of these five things well, we encourage you to apply. We care more about evidence of ownership, learning, and shipped outcomes than a perfect keyword match.

Nice to have

• Experience with manufacturing, supply-chain, ERP, PLM, MES, quality, or industrial data.
• Experience with AWS and modern data technologies such as dbt, Airflow or Dagster, Kafka or similar event systems, and cloud warehouses or lakehouses.
• Experience designing metrics layers, analytical data products, or operational reporting used by frontline teams.
• Familiarity with enterprise security, regulated environments, air-gapped networks, or customer-managed infrastructure.
• Experience in a customer-facing technical role such as forward deployed engineering, solutions architecture, technical consulting, or implementation engineering.

Benefits & Perks

First Resonance participates in E-Verify. As part of our onboarding process, a new hire's Form I-9 information will be shared with the federal government to confirm they are authorized to work in the U.S.

Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location.