Senior Analytics Engineer

Description

The company makes a personal finance product that helps members understand their money and save time and money through a set of services.

The Analytics Engineering team keeps data consistent and trustworthy. It builds the dimensional models behind business decisions and is responsible for the integrity of that data.

Analytics Engineers work in a semi-embedded setup, close to the Data Analyst teams they support while staying part of a central Analytics Engineering practice. The work involves turning business questions into technical requirements, shaping ingested source data into forms the business can use, and working with engineering teams on the upstream data the team relies on.

The company is hiring a Senior Analytics Engineer to help shape the architecture as it grows. You will build and evolve the star schema so Data Analysts and stakeholders across the business can run their own analysis with confidence. Strong data literacy across the company is a stated goal of this work.

Responsibilities

• Design and build dimensional models that scale, using dbt and BigQuery.
• Turn unclear business questions into dimensions, facts, and grain decisions that stay valid as the business changes.
• Weigh normalization, performance, and usability against each other, and write down the reasons for each choice.
• Reduce technical debt in the dbt project across model layers, naming and testing standards, macro reuse, and incremental strategy.
• Own data quality and monitoring for the models you build, including defining what correct means for each model and setting up checks for it.
• Build and improve alerting and triage so data issues surface before stakeholders find them.
• Lead root-cause investigations of data discrepancies from the source event or system of record through to the analytics layer.
• Work with Data Engineering and product engineering on upstream contracts and instrumentation quality.
• Link source data to business definitions and help define core business measures, aligning stakeholders when they disagree.
• Work with Data Analysts and BI so models support self-service analysis.
• Convert business needs into technical requirements and set priorities for them.
• Raise the team's standard through code review, design review, and documentation.

Requirements

• 5+ years in analytics engineering, data engineering, or a related role.
• Deep dimensional modeling experience, including designing models from scratch and fitting them into a coherent analytics architecture. You understand grain, SCD types, and fact table tradeoffs.
• Experience with complex modeling cases: conforming dimensions across use cases, many-to-many relationships, late-arriving and restated data, and keeping models usable as source systems change.
• You treat data quality as a design problem. You have built tests and monitoring into pipelines, agreed SLAs or expectations with data owners, and handled on-call and triage.
• You measure your work by how useful it stays to stakeholders over time, not by delivery speed, architectural elegance, or how well it serves one immediate need.
• Production dbt experience, including materialization strategies, testing, macros, and keeping a large project maintainable.
• 2+ years with BI tools, Looker preferred, and an understanding of how modeling choices limit or enable what the analytics layer can do.
• Strong cross-functional communication and the ability to influence business and stakeholder decisions.
• Strong problem decomposition: you can find the real problem behind a request and fit it into the modeling roadmap and architecture.
• Nice to have: experience with finance or financial services data, such as transactions, subscriptions, revenue recognition, ledgers, or reconciliation against a system of record.
• Nice to have: experience with the company's stack, which includes BigQuery, dbt Cloud, Looker, Amplitude, and DeepNote.
• Nice to have: experience with data governance, lineage, or catalog tools.
• Nice to have: familiarity with Agile and sprint cycles.
• Nice to have: experience in mobile app or product analytics.

Conditions

Salary range is $150,000 to $190,000, plus bonus and benefits. Base pay depends on job-related knowledge, skills, and experience.

Unlimited PTO.

Commuter benefits apply to in-office work only.

San Francisco Fair Chance Ordinance: the company will consider qualified applicants with arrest and conviction records.

Benefits

• Health, dental, and vision plans.
• Life insurance.
• Long-term and short-term disability coverage.
• Competitive pay.
• 401k matching.
• Team Member Stock Purchasing Program (TMSPP).
• Learning and development opportunities.
• Tuition reimbursement.
• Unlimited PTO.
• Daily lunch, snacks, and coffee, in-office only.
• Commuter benefits, in-office only.