Data Operations Engineer, Product Lifecycle Operations

We are looking for a Data Operations Engineer to architect, build, and deploy critical operational tooling across our diverse portfolio. In this role, you will function as the bridge between the CEO Office and the divisional product teams designing, building, and deploying both hardware and software across the business. You will develop tailored analytics solutions for each product team that also provide a consolidated view of their disparate datasets for centralized executive reporting. You will not just visualize existing data - you will weaponize it to diagnose critical blind spots, identify opportunities for connection, and drive systematic data integrity. You will translate operational questions into metrics, dashboards, and analyses that inform executive decision-making. The ideal candidate will have a mix of both business and technical acumen, with a strong focus on thoughtful system design in high visibility, heavily cross-functional environments. Prioritization of scrappy, easily adoptable solutions with an actionable roadmap for improvement over flawless, fully baked system architecture is a critical success factor.

Responsibilities

Own the technical roadmap from conception through delivery to sustainment, connecting core enterprise systems (ERP, PLM, MES, etc) with tactical collaboration tools (Jira, Airtable, etc) to provide a single source of truth; Partner cross-functionally to deeply understand tools, taxonomies, and ontologies, and collaborate to develop applications that create coherence across the tech stack; Build custom dashboards and analytical tools for divisional product teams and senior leadership; Leverage both technical and operational data to drive business outcomes, transforming raw data into actionable insights; Create and iterate on solutions that last, starting scrappy, collecting stakeholder feedback, then formalizing and optimizing; Facilitate documentation and knowledge transfer so architecture decisions, dependencies, and assumptions remain accessible and durable

Requirements

6+ years of experience in data analytics, software engineering, management information systems, or similar; Direct coding experience, using Python, SQL, React, TypeScript, or similar; Deep understanding of data stack tools like Palantir Foundry or Databricks; Direct experience owning, leading, and driving adoption of user-facing applications and associated processes; Proven track record of leveraging technical data to solve business problems; Demonstrated technical autonomy from roadmap definition to solution rollout and sustainment; Proven ability to execute operationally while also being able to step back and think strategically; Eligible to obtain and maintain an active U.S. Secret security clearance; Preferred: Experience connecting data across business, engineering, and manufacturing environments (CRM, ERP, PLM, MES, etc); Preferred: Experience building end-to-end data pipelines, ontologies, and applications in Palantir Foundry or Databricks

Nice to have

Experience connecting data across business, engineering, and manufacturing environments (CRM, ERP, PLM, MES, etc); Experience building end-to-end data pipelines, ontologies, and applications in Palantir Foundry or Databricks

Benefits

Highly competitive equity grants (included in the majority of full time offers); Comprehensive, competitive benefits package (available at little to no cost to employees) covering health, recovery, and more