instructure

Senior Analytics Engineer

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Posted within 60 days ·

  • remote
  • FullTime
  • General & Administration
  • US-REMOTE
Work arrangement
remote
Employment
FullTime
Stated compensation
USD 145,000–155,000 1 YEAR
Stated sponsorship
Not stated
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Remote policy
remote
“Provider workplace type: remote”
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Geographic scope
US
“Provider location: US-REMOTE”
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Minimum experience (years)
5
“5+ years of experience in analytics engineering, data engineering, or a similar role.”
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Employment type
FullTime
Compensation
USD 145,000–155,000 1 YEAR
6 fields not stated in this posting
Employer sponsorship
Not specified
Degree requirement
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Security clearance
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Citizenship requirement
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

Reading view uses normalized posting text so exact evidence excerpts can be highlighted.

At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers. We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in: We're hiring a Senior Analytics Engineer to build the data models that teams across Instructure use to run the business. You'll work in dbt and Snowflake every day. You'll also sit in the room with business leaders, understand the decisions they're making, and design data that answers their questions correctly the first time.
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This role is broad by design. You'll support analytics across Finance, Operations, Product Management, Sales, and other parts of the company, so you'll see how the whole business fits together. It suits someone who writes clean SQL and also asks "what is this number used for?" before building it. You'll own models from source to dashboard, and you'll help set the standards for how we design, test, and document our data. What you'll do 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. What you bring 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. Nice to have Experience modeling data from CRM and other business systems such as Salesforce. Familiarity with orchestration tools such as Airflow or dbt Cloud. Experience with a BI tool such as Tableau, Looker, or Power BI. Background in a SaaS or education technology company. What success looks like 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. Get in on all the awesome at Instructure! 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.
Original formatting and links

At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.
We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:

We're hiring a Senior Analytics Engineer to build the data models that teams across Instructure use to run the business. You'll work in dbt and Snowflake every day. You'll also sit in the room with business leaders, understand the decisions they're making, and design data that answers their questions correctly the first time.

This role is broad by design. You'll support analytics across Finance, Operations, Product Management, Sales, and other parts of the company, so you'll see how the whole business fits together. It suits someone who writes clean SQL and also asks "what is this number used for?" before building it. You'll own models from source to dashboard, and you'll help set the standards for how we design, test, and document our data.

What you'll do

  • 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.

What you bring

  • 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.

Nice to have

  • Experience modeling data from CRM and other business systems such as Salesforce.

  • Familiarity with orchestration tools such as Airflow or dbt Cloud.

  • Experience with a BI tool such as Tableau, Looker, or Power BI.

  • Background in a SaaS or education technology company.

What success looks like

  • 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.

Get in on all the awesome at Instructure!

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.

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