[Remote] Staff Data Engineer
Note: The job is a remote job and is open to candidates in USA. Foley is a modern SaaS company that focuses on improving how safety-sensitive industries hire and manage risk. They are seeking a Staff Data Engineer to design and scale data systems, lead the development of data pipelines, and ensure data governance across the organization.
Responsibilities
- Lead the design and evolution of Foley’s enterprise data architecture
- Contribute to the ongoing development of our Enterprise Data Model
- Define standards and best practices for data modeling, storage, access, and reliability
- Drive architectural decisions that balance scalability, maintainability, and performance
- Design, build, and maintain scalable data pipelines across internal systems, vendor platforms, and the data warehouse
- Improve data quality, observability, and reliability across core workflows
- Optimize data workflows for efficiency and long-term operational health
- Support both batch and event-driven or CDC-based pipeline patterns
- Own schema design and warehouse modeling strategy, including dimensional and normalized approaches where appropriate
- Help define and implement data governance best practices, including RBAC
- Ensure shared definitions, documentation, and trust in core business data
- Serve as a thought partner to Engineering, Product, Analytics, and business teams
- Translate technical complexity into clear recommendations and tradeoffs
- Raise the bar for data engineering practices across the organization
- Help the company make better decisions through strong, accessible data foundations
- Identify opportunities to improve workflows through automation, tooling, and thoughtful use of AI
- Experiment pragmatically with new technologies and scale what works
- Build systems and guardrails that enable teams to move faster without sacrificing quality
Skills
- Strong experience building and maintaining production ETL/ELT pipelines
- Experience working across both batch and streaming / CDC / event-driven data environments
- Proven ability to design scalable warehouse schemas and data models in a layered architecture
- Deep knowledge of database architecture and distributed data systems
- Experience with cross-system entity resolution and complex data modeling
- Experience implementing data governance standards, including RBAC
- Strong software engineering fundamentals, including reliability, backend systems, and data processing
- Ability to operate at a Staff level, setting direction and influencing across teams
- Strong experience with Python, SQL, and AWS data tooling including Redshift, Glue, Lambda, S3 and Data Orchestration (e.g. Airflow)
- Experience supporting ML or LLM-related pipelines in production
- Familiarity with multi-step agent orchestration frameworks such as LangGraph
- Experience partnering with Data Science teams to operationalize data products
- Experience helping organizations introduce AI-enabled workflows in a thoughtful, production-oriented way
Benefits
- Medical, dental, and vision coverage
- A 401(k) with company match
- Paid time off and holidays
- Wellness programs
- An employee assistance program
Company Overview
Company H1B Sponsorship