What are the responsibilities and job description for the Lead Data Enginer position at Staffing Science?
Lead Data Engineer (Principal-Level)
- 4 days a week on site in Los Angeles (flexible start/end times if needed)
- The company has a free gym on site and a modern office that includes outdoor workspaces.
- Must be a U.S. citizen or Green Card Holder
Los Angeles, CA (Hybrid – 4 days onsite)
We’re partnering with a fast-growing, mid-size product-driven company that’s investing heavily in modern data infrastructure, AI, and self-service analytics.
This is a high-impact, principal-level role where you’ll operate at the intersection of data architecture, business strategy, and hands-on engineering—owning the evolution of their data platform and helping the business actually use data to make decisions.
The Opportunity
This is not a heads-down execution role.
You’ll step in as the technical and strategic leader of the data function, balancing a team of strong executors with architecture, stakeholder alignment, and business-facing leadership.
The company is currently running a split data environment (Snowflake BigQuery) and is about to undergo a major consolidation into Snowflake on AWS, followed by a full dbt implementation to enable a scalable, self-service analytics model. You’ll own that transformation.
What You’ll Own
- Lead the migration from a fragmented data stack (BigQuery Snowflake) into a unified Snowflake (AWS) environment
- Architect and implement dbt from the ground up to support scalable, governed data modeling
- Design clean, business-ready data models that drive decision-making across teams
- Partner directly with executives, product, and business stakeholders to translate needs into data solutions
- Establish source-of-truth frameworks and eliminate conflicting metrics across systems
- Guide best practices across data modeling, transformation, and documentation
- Support a shift toward self-service analytics AI-driven workflows
- Collaborate with engineering on data pipelines, performance, and scalability
- Act as the bridge between technical teams and the business
What Makes This Role Different
- Highly visible, business-facing (not just backend engineering)
- You’ll balance a team of strong IC executors who need architectural direction
- Opportunity to own a full data platform transformation
- Company is actively embracing AI tooling (including Claude and similar)—they want someone who leans into it, not against it
- Real opportunity to shape how the company uses data at scale
What They’re Looking For
Must-Have Technical Experience
- Strong experience with:
- Snowflake (required)
- AWS (required)
- dbt (or deep transformation-layer experience)
- Experience designing and scaling modern data warehouse architectures
- Strong SQL Python for scripting and data workflows
- Experience working across multi-source, complex data environments
Leadership & Business Skills (Critical)
- Proven ability to work directly with stakeholders and business leaders
- Strong communication and data storytelling skills
- Ability to translate messy business problems into clean data solutions
- Experience acting as a technical lead, architect, or principal-level IC
- Comfortable balancing strategy with hands-on execution
Nice to Have
- Experience with BigQuery (migration context)
- Exposure to AI tools (Claude, LLM workflows, etc.)
- Background in building self-service analytics ecosystems