F
First Resonance
Forward Deployed Engineer (Data)
Skills
SQL QueriesData EngineeringPythonKafkaGitData AnalysisAWSdbtApache AirflowSupply Chain
15 days ago
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Important information
Contract type:
Permanent
Salary:
$150,000 – $190,000 / year
Location:
Los Angeles, CA, USA
Work mode:
Onsite
Published on:
5 October 2026
What they need
- 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
- 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
Benefits
- Medical, dental & vision
- Generous life and disability insurance for you and your family
- Flexible PTO
- 401K retirement plan with employer match
- Other financial benefits and services to give you financial peace of mind
- Equity
- Up to 16 weeks of parental leave
- Flexible spending accounts
- Work-from-home setup
- Remote & hybrid options (role dependent)
- Amazing office in Downtown LA- 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
- 5+ years of experience in data engineering, software engineering, analytics engineering, or another role building production data systems
- Ability to work directly with customers, turn ambiguous operational problems into clear technical plans, and communicate tradeoffs to both engineers and business leaders
- Sound judgment around distributed-system and data-quality failure modes, including idempotency, ordering, schema evolution, reconciliation, observability, and access control
- Experience building and operating data pipelines across APIs, transactional databases, event streams, object storage, and cloud data platforms
- Strong programming ability in Python and fluency with SQL, data modeling, and software-engineering practices such as testing, version control, and code review
- Experience with manufacturing, supply-chain, ERP, PLM, MES, quality, or industrial data
- Experience designing metrics layers, analytical data products, or operational reporting used by frontline teams
- Experience with AWS and modern data technologies such as dbt, Airflow or Dagster, Kafka or similar event systems, and cloud warehouses or lakehouses
- 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
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