Job Opportunities API

We are looking for a Staff Data Engineer to design, build, and scale the data systems that power how Foley operates and grows. In this role, you will lead the development of reliable data pipelines, shape our enterprise data architecture, and establish high standards for how data is modeled, governed, and accessed across the organization. This is a highly strategic and hands-on technical leadership role. You will be the most senior data engineering voice on the team, partnering closely with Engineering, Product, Analytics, and business stakeholders to ensure our data systems are scalable, trusted, and built for long-term impact. The ideal candidate combines strong data architecture depth with practical execution. They should be able to operate independently, navigate ambiguity, and make sound technical tradeoffs in a fast-moving environment. WHAT YOU’LL DO DATA ARCHITECTURE AND STRATEGY - 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 PIPELINE DEVELOPMENT AND EXECUTION - 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 DATA MODELING AND GOVERNANCE - 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 CROSS-FUNCTIONAL TECHNICAL LEADERSHIP - 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 INNOVATION AND CONTINUOUS IMPROVEMENT - 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 WHO YOU ARE - 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). NICE-TO-HAVES - 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 YOU MIGHT THRIVE IN THIS ROLE IF YOU - Think in systems and tradeoffs, not just tools - Enjoy solving ambiguous data problems and turning them into scalable solutions - Can communicate clearly with bot