Analytics Engineering Team Lead

Lead and grow the team. Set priorities, coach, and keep a steady delivery rhythm across analytics engineering and web analytics.

Own the semantic layer. Design, build and evolve SQL-based models and metric definitions so that one number means one thing across all our products.

Raise data curation and automate the routine. Move the team from ad hoc requests to reusable, tested, documented datasets that people and our AI data assistant can query directly, with tracking checks and data-quality monitoring on autopilot.

Set standards and partner across the data organization. Modeling conventions, version control, testing and release practices, code review; work with Data Business Partners, Data Science / ML and Data Platform on scope and ownership. Stay close to the code on critical builds.

Experience. 5+ years in analytics, data or BI engineering, including 2+ years leading a team or leading others technically.

Expert SQL and Python. You set query and performance standards others follow, rewrite expensive queries and explain the trade-offs, handle incremental loads, deduplication and slowly changing dimensions, and own production Python components that other teams depend on.

Data modeling and pipelines. You design warehouse and mart models that several teams build on, including a semantic layer, and choose the methodology (star schema, Data Vault or equivalent) to fit the queries it must serve. You optimize and troubleshoot pipelines on a cloud stack such as AWS (Athena, Redshift, Glue) and orchestration tools such as Airflow.

Engineering discipline. You set branching and code review standards, require schema and data tests and CI before release, and lead risky changes with a clear rollout and rollback plan.

Data quality and data fluency. You design validation that catches problems before stakeholders do, fix root causes rather than symptoms, set documentation standards, and investigate unfamiliar sources before trusting them.

Business impact. You design solution options for complex problems, split cross-team work into pieces with a clear definition of done, build dashboards around the decision they support, and become a trusted partner to business leaders.

AI in everyday work. You redesign team workflows around AI tools to drive adoption, and evaluate AI outputs for quality, privacy and bias.

Leadership and ownership. You own complex team-level projects, make high-impact decisions from complex information, coach people by spotting skill gaps and giving regular feedback, set clear scope expectations, and turn change into actionable steps for the team.

Communication. You clarify complex ideas, build consensus across teams and time zones, and communicate in fluent English.

Nice to have: experience with dbt or a similar transformation framework (we may adopt one); web analytics and tracking (GTM, GA4); B2B SaaS or document-workflow / e-signature background.