Data Engineering Lead

Seer Interactive is a digital marketing consultancy that harnesses compassion, data, technology, and AI to make a mark on our communities, our coworkers, our clients, our industry, and our neighbors. We relentlessly pursue (and share) the truth, bringing together millions of data points from quantitative and qualitative sources, enhanced by responsible, human-centered AI. Our purpose is to unlock potential across these communities, envisioning a world where doing the right thing is intuitive and informed.

At Seer, we see AI as a catalyst for innovation, collaboration, and creativity. Regardless of your division or discipline, leveraging AI is a core part of how we deliver smarter, faster, and more strategic outcomes for our clients. Our AI Council drives company-wide integration by focusing on education, purposeful implementation, and continuous learning, ensuring that AI is embedded in how we think, operate, and grow.

If you’re ready to uplift others, challenge your ego, commit to the truth, and be better than yesterday—keep reading.

Seer is a remote-first agency and a Certified B-Corp, with team members across the country. If an office environment is more your style, this position can also sit in our HQ office in Philadelphia. We can only consider candidates based in the US who can work continental US-based hours.

You, the Data Engineering Lead of our dreams, are the technical architect of Seer’s data platform, and building agentic development workflows is a core part of the job. You’ll own the structural data foundation behind our analytics and AI products while finding repetitive data and BI work and designing, shipping, and maintaining agents that take it off people’s plates.

At Seer, AI is embedded in how we deliver smarter, faster, and more strategic outcomes, and the modern marketing data stack is evolving past the dashboard. You’re excited to help shape it. You design platforms that let strategists, analysts, and LLMs query the same source of truth and arrive at better answers via a well-governed semantic layer. You make the engineers around you better through mentorship, code review, and pairing, and you teach in a way that sticks long after a project ends.

You’re intellectually curious, systems-minded, and not afraid to refactor a legacy DAG, rewrite a tangled query, or push back on a flawed plan. Knowing which battles to pick as you shape the future of Seer’s data structure is a core part of the job.

• Set the technical direction for Seer’s data platform by defining the architecture and the standards that other engineers build toward.
• Own Seer’s data platform end-to-end across Big Query, Dataflow, Airflow, Cloud Run, Cloud Functions, Cloud Storage, and ingestion tools like Fivetran, while making the cost, latency, and freshness tradeoffs that let us scale without surprises.
• Set the standard for how we model and serve data. This runs from dimensional modeling (grain, conformed dimensions, slowly changing dimensions) and dbt incremental models to a governed LookML semantic layer with row-level security, surfaced in our embedded Looker interface and via MCP.
• Structure data for agents to retrieve correct, deterministic answers to natural language questions from our non-technical team members.
• Automate the routine work around dbt: generating tests and documentation, assessing the downstream impact of schema changes, and producing migration or backfill plans.
• Build triage agents that read pipeline failures and data quality alerts, trace the cause through logs and lineage, and fix the issue or recommend a fix within established operational guardrails.
• Tune what’s expensive: evolve the observability layer from a manual process to ai-powered workflows that hunt down…