Senior Analytics Engineer
RemoteUnited States
Job Summary
Partner with the Commercial team to design data solutions that enable customers to inform critical business decisions with zero friction. Manage end-to-end data product releases, prioritizing tasks and project-managing cross-functional teams to ensure accurate, reliable, and on-time delivery. Develop strategic product improvements that maximize data quality and business impact while building systems to proactively monitor pipeline integrity. Perform root-cause analyses on data quality issues, find scalable solutions, and propose methodology improvements. Report to the VP of Data Operations in a remote-first environment during US business hours.
Required Qualifications
- 6+ years of hands-on experience in data-focused roles
- Expert in SQL
- Expert in DBT (or similar)
- Expert in Excel
- Expert in business intelligence tools (e.g. Looker, Redash)
- Expert use of AI to streamline data workflows and elevate data product reliability — without adding QA overhead
- Proven ability to organize, analyze and vet large volumes of data with great attention to detail
- Comfortable making defensible judgment calls in gray areas: you can tell a genuine data-quality issue from a real signal in the data, use hypothesis testing to rule out sources of discrepancy, and run root-cause investigations that stop the problem from recurring
- Strong communication and stakeholder management skills; able to translate technical concepts and align Data Ops initiatives with customer-centric objectives
- Passionate about solving customer problems
- Self-starter with the ability to carry multiple initiatives, prioritize time and resources, and meet deadlines in a fast-moving environment
- Experience mentoring or supervising teammates and upholding best practices in data operations
- Candidates who can work during US business hours
- Preferably, you should be based in a US time zone (Eastern, Central, Mountain, or Pacific)
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