Responsibilities
- Design, build, and maintain scalable data pipelines for clients across industries
- Architect and optimize cloud data warehouse solutions, adapting to each client's stack, which may include Snowflake, BigQuery, Redshift, Microsoft Fabric, or similar platforms
- Lead data integration projects from source system to analytical layer, including scoping, delivery, and handoff
- Work fluidly across a range of modern data tools and platforms as client engagements demand, picking up new technologies quickly and applying best practices regardless of the toolset
- Collaborate with analysts and data scientists to ensure data is clean, reliable, and well-modeled
- Champion data quality, testing, and observability best practices across client engagements
- Produce and maintain clear technical documentation including pipeline architecture, data dictionaries, lineage maps, and runbooks so clients can understand and own their infrastructure long-term
- Document engineering decisions, standards, and workflows in a way that supports knowledge transfer to both clients and junior team members
- Research and evaluate new technologies and advocate for tooling investments that benefit the firm
- Train and mentor junior team members on engineering standards, pipeline design, and best practices
- Participate in client-facing communication, including requirements gathering and progress updates
- Flex support when capacity allows: contribute to analyst-side deliverables such as Power BI dashboard development, ad-hoc reporting, or data visualization
Work Arrangement
Hybrid
Team
Team size: lean team. Structure: client-facing role that combines deep technical execution with strategic thinking
Additional Information
- Initial onboarding will be onsite
- For certain client projects, there may be a need to be in person or for limited travel to client offices
- Candidate must reside in the United States
