Data Engineer - Los Angeles, CA or Seattle, WA
Los Angeles, Los Angeles County, California, 90079, USA
Listed on 2026-01-07
-
Software Development
Data Engineer
About Re:
Build Manufacturing
Re:
Build Manufacturing is a growing family of industrial and engineering businesses combining enabling technologies, operational superiority, and strategic M&A to build America’s next generation industrial company. At Re:
Build we deploy deep expertise in engineering, operations management, and technology to supercharge the performance of our member companies. We leverage deep professional expertise and a candid, principled operating culture to drive differentiated outcomes. Ours is a fast-paced environment where individuals can stretch and be challenged to pursue their fullest potential.
Re:
Build was founded to pioneer a profitable model for the revitalization of US manufacturing. We’ve assembled a powerful set of complimentary capabilities and lines of business that enable us to pursue a wide range of end markets. Our acquired businesses are grounded in build-to-print and by-the-hour engineering and design services, and we’re leveraging their combined expertise to migrate to increasingly sophisticated program development and production, as well as the generation of our own products.
Our unique set of capabilities lend themselves to highly complex systems and products, and we offer customers a range of services including product and systems design, automation, fabrication, assembly, and large volume contract manufacturing. Our customers span a wide array of industries including aerospace, defense, mobility, healthcare, pharma, biotech, clean tech, chemicals, energy, lifestyle, food production, and industrial equipment.
The Data Engineer will focus on utilizing modern data technologies to operationalize and expand the enterprise Data Lake. This role centers on implementing efficient ingestion strategies, integrating diverse data sources, and ensuring data is structured for accessibility and analysis. The engineer will work across hybrid environments—on-prem and cloud—to automate data movement, validate data quality, and enable analytical teams to derive insights from trusted, well-organized datasets.
This position requires hands‑on technical depth in data ingestion and transformation, along with the analytical understanding needed to align data availability with business and reporting needs.
- Work Week:
Remote - anywhere across the USA. - Hours:
Due to working remote and the team being based in Los Angeles, CA we require this hire to work either MST hours or PST hours. - Travel Required:
There is quarterly travel required for meetings that are held onsite in Los Angeles, CA and occasionally travel to a company location as needed.
Build’s Compensation Philosophy
- Competitive Base Pay
- All Re:
Build Employees are eligible for performance-based bonus - All Re:
Build Employees receive Re:
Build incentive stock awards, annual - Competitive, Comprehensive Benefits Plan.
- Exciting opportunity to work in a multi-site high-tech manufacturing conglomerate.
- Impactful role, and one in which you will enjoy considerable autonomy and variety.
- Investor-backed business to support growth.
- Financial rewards.
- Enormous learning experience and the opportunity to acquire additional responsibilities over time.
- Co-design
data interfaces and pipelines
in close collaboration with software engineers and technical leads, ensuring alignment with application domain models and product roadmaps. - Build and operate
batch, streaming, and change data capture (CDC)pipelines from diverse sources (ERP, CRM, Accounting, knowledge repositories, and other enterprise systems) into the data lake.
- Model curated data within the lake into
data warehouse structures
(e.g., star schemas, wide tables, semantic layers) optimized for
business intelligence (BI),
ad-hoc analytics
, and
key performance indicator (KPI)reporting. - Publish
certified datasets
and
policy-aware retrieval assets
(tables, document embeddings, vector indexes) to enable
analytics
,
AI
, and
retrieval-augmented generation (RAG)use cases.
- Establish robust
data observability
and
quality checks
to ensure reliability and consistency. - Apply
governanc…
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