Senior Analytics Engineer

Design, build, and maintain dimensional models in dbt and Snowflake that support reporting and analysis across Finance, Operations, Product Management, and other business functions.

Translate business questions into clear data requirements by working directly with senior leaders across the company.

Own the full model lifecycle: source ingestion patterns, staging, intermediate and mart layers, tests, documentation, and deployment.

Set and enforce modeling standards, including naming conventions, grain definitions, slowly changing dimension handling, and testing practices.

Tune Snowflake performance and cost through smart materialization choices, clustering, and warehouse sizing.

Partner with data engineers and business systems teams to make sure upstream data arrives in a shape we can model well.

Review pull requests, mentor analysts and engineers, and raise the quality bar across the team.

Explain data definitions and tradeoffs to non-technical audiences in plain language, and push back when a request would produce a misleading metric.

5+ years of experience in analytics engineering, data engineering, or a similar role.

A bachelor's degree in Computer Science, Information Systems, Finance, or another quantitative field is preferred.

Deep, hands-on experience with dbt, including macros, packages, incremental models, snapshots, and testing.

Strong Snowflake skills, with advanced SQL and a good sense of performance and cost.

Proven experience designing dimensional models (star schemas, facts, dimensions, conformed dimensions) and a clear point of view on when to use them and when not to.

Solid data architecture instincts: layered modeling, grain, lineage, data contracts, and maintainable project structure.

Working knowledge of how a business operates across functions such as finance, sales, operations, and product, ideally in a SaaS company.

The ability to hold a credible conversation with directors, VPs, and executives about business issues, and to turn that conversation into a data solution.

Strong written and verbal communication. You document your work and explain it well.

Experience with Git-based workflows and CI/CD for data projects.

In 90 days, you've shipped your first production models and built working relationships with partners in several business functions.

In 6 months, you own a major domain in our data model and the business trusts the numbers it produces.

In a year, you've shaped our modeling standards and made the whole team faster.

We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.

Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.

Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.

Comprehensive wellness programs and mental health support

Learning and development resources, including professional development tools and tuition reimbursement, to support your growth

The technology and tools you need to do your best work

Motivosity employee recognition program

A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.