Senior Analytics Engineer

Role overview

Join a small, growing analytics function and build the data foundation used for decisions across finance, go-to-market, product, engineering, customer success, and other teams. This senior individual-contributor role combines analytics engineering, data-product ownership, stakeholder partnership, and technical leadership. You will turn ambiguous business questions into reliable models, metrics, self-service tools, and durable operating standards.

Responsibilities

- Own and evolve analytical data models, transformation pipelines, metric definitions, semantic layers, and self-service reporting experiences. - Design scalable dbt-based transformations and improve the reliability, performance, observability, and quality of ELT workflows. - Partner directly with business stakeholders to clarify problems, define requirements, explain tradeoffs, and deliver usable technical solutions. - Build dashboards, analytical tools, documentation, and enablement resources that help teams explore data confidently without constant assistance. - Manage the full lifecycle of data products, including discovery, implementation, testing, deployment, monitoring, governance, access controls, and iteration. - Investigate data-quality and technical issues, drive root-cause fixes, mentor teammates, and identify automation or platform investments for the analytics roadmap.

Requirements

- At least 5 years of experience in analytics engineering, data engineering, business intelligence engineering, or a closely related field. - Record of leading cross-functional data initiatives from unclear problem definition through delivery, adoption, and measurable impact. - Advanced SQL skills and deep experience designing and operating analytical models and pipelines. - Strong hands-on experience with dbt, testing, version control, documentation, orchestration, observability, and data-quality practices. - Experience with modern ELT and activation tools such as Fivetran and Hightouch, or comparable technologies. - Experience with cloud data warehouses; Google Cloud Platform and BigQuery are strongly preferred.

Nice to have

- Experience with BI or semantic-layer tools such as Omni, Looker, Sigma, Tableau, Mode, or Hex. - Practical use of AI in data, analytics, engineering, or business workflows with sound judgment about appropriate applications. - Python or another quantitative programming language. - Experience in a startup or high-growth environment and comfort working independently amid changing priorities.

Benefits and work setup

- Published base salary range: $140,000–$165,000 USD. - Remote-first work with team meetups, twice-yearly destination summits, and a monthly coworking, phone, and internet stipend. - Stock options, potential participation in secondary offerings, and an extended exercise period. - Company-paid health, dental, and vision coverage for employees and dependents. - Flexible time off and paid parental leave.