Lead Data Platform Architect: Build from Scratch Job Los Angeles area,California USA,IT/Tech

Requirements

8+ years of experience in data engineering, data infrastructure, or related fields, with 3+ years building and leading data engineering teams
Strong hands-on skills in modern data stack technologies: data warehousing (Snowflake, Big Query, Redshift, or similar), ETL/ELT pipelines, data modeling, and orchestration tools (Airflow, Dagster, or similar)
Experience building data platforms from scratch, not just maintaining or extending existing ones
Track record of hiring and developing high-performing engineering teams in fast-paced environments
Ability to work across the full stack of data engineering: from source system connectivity and pipeline reliability to data modeling and serving layer design
Strong communication skills and comfort working with stakeholders across technical and non-technical functions to understand requirements and set priorities
(Desirable) Experience in aerospace, defense, or manufacturing environments where data spans engineering tools (PLM, MBSE, CAD/CAM) and enterprise systems (ERP, project management)
(Desirable) Background working with AI/ML teams as a data platform provider, with an understanding of what those teams need from the data layer
(Desirable) Experience connecting complex, heterogeneous source systems with different schemas, update cadences, and access patterns
(Desirable) Familiarity with data governance and data quality practices, and experience building organizational trust in data products
(Desirable) Prior experience at a company poised for aggressive growth where the data platform had to scale ahead of demand
(Desirable) Active U.S. security clearance at any level

What the job involves

True Anomaly does not have a central data platform today
Data lives in disconnected systems: PLM, ERP, project management, source control, and documentation tools, with no warehouse, no unified data model, and no programmatic access layer
As Senior Manager of Data Engineering, you will build this capability from scratch: the platform, the pipelines, the team, and the operating model
Your first priority is enabling the AI Platform Engineering team, which depends on a reliable data foundation to deliver on the company’s top strategic priority
Beyond AI, the data platform will serve engineering, programs, manufacturing, and business operations across the company
This is a player-coach role
You will be writing code and making architecture decisions on day one while simultaneously hiring and developing a high-performing team
Build the data engineering function from zero: design the data platform architecture, stand up the initial infrastructure, and start delivering value before the team is fully hired
Hire and lead a team of 5 data engineers, recruiting top-tier technical talent who thrive in ambiguous, fast-moving environments
Design and build the company’s data warehouse, unified data model, and pipeline infrastructure, connecting systems like PLM (Teamcenter), ERP (Net Suite), Jira, Git, and Confluence into a single reliable data layer
Partner closely with the AI Platform Engineering team to provide the data infrastructure they need as a critical-path dependency for the company’s AI strategy
Serve as the technical authority for data architecture decisions during the team’s formative period: technology selection, data modeling patterns, pipeline design, and the foundational choices the rest of the team will build on
Work across the company to understand data needs from engineering, programs, manufacturing, and business operations, and translate those into a platform that serves all of them

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