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Analytics Engineer

Remote (United States)

Pay
Pay not listedSimilar roles state $122K–$190K
Work setting
Remote — work setting source
Listed location: Remote (United States)
Work setup in the employer’s posting: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: SALARIED_FT
From the employer’s posting
Apply at Harbor Compliance

What you’ll work on

Full posting
  • Build and maintain tested, documented dbt models in Snowflake

  • Partner with stakeholders to turn vague asks into defined problems

  • Create dashboards, explorations, and self-serve datasets in BI tools

  • Define and maintain shared metric definitions and resolve discrepancies

  • Add tests, monitoring, and alerting to catch data issues early

From the employer’s posting
Build and maintain clean, tested, documented dbt models in Snowflake
Work directly with teams across the company to understand what they're trying to accomplish
Create dashboards, explorations, and self-serve datasets in our BI tools
Define and maintain a shared set of metric definitions, document them, and resolve discrepancies when numbers don't match
Add tests, monitoring, and alerting so we find data issues before our stakeholders do

What you’ll bring

All qualifications

Core experience

  • 3–5 years in analytics engineering, data engineering, or similar
  • Strong SQL, including CTEs and window functions
  • Hands-on dbt and a cloud warehouse, ideally Snowflake
  • Python for data work and automation
  • Experience with a modern BI tool such as Metabase, Hex, Sigma, Omni, Looker or Tableau
Qualification wording
3–5 years in analytics engineering, data engineering, or a similar role
Strong SQL: fluent in CTEs and window functions
Hands-on dbt and a cloud warehouse, ideally Snowflake
Python for data work and automation
Experience with a modern BI tool (Metabase, Hex, Sigma, Omni, Looker or Tableau)

Tools in this posting

  • Python
  • SQL
  • Airbyte
  • dbt
  • Fivetran
  • Looker
  • Metabase
  • Sigma
  • Snowflake
  • Tableau
  • Airflow
  • Dagster
Source — Tool mentions in context
- Hands-on dbt and a cloud warehouse, ideally Snowflake, with a solid grasp of modeling patterns, testing, and documentation. - Python for data work and automation. - Experience with a modern BI tool (Metabase, Hex, Sigma, Omni, Looker or Tableau) and the speed to pick up the others.
- Ship like an engineer. Use Git, pull requests, code review, and CI to make changes safely and repeatedly. - Use AI to move faster. Apply AI tools in your daily workflow for writing and reviewing SQL, documentation, exploration, and debugging, and help the team figure out where AI genuinely helps and where it needs a human check. - Improve the program. Help define the best practices, standards, and documentation the team follows as we build out our analytics practice.
- 3–5 years in analytics engineering, data engineering, or a similar role. - Strong SQL: fluent in CTEs and window functions, and able to untangle someone else's query. - Hands-on dbt and a cloud warehouse, ideally Snowflake, with a solid grasp of modeling patterns, testing, and documentation.
Skills and Knowledge - Fluency with SQL and working knowledge of dbt + lakehouse workflows - Working knowledge of BI/Viz tools
- Nice to haves: - - Airbyte or another ingestion/orchestration tool (ex: Airflow, Dagster) - Experience building a semantic layer (dbt Semantic Layer, Omni, LookML, or similar), especially one that serves both humans and AI agents.
- Working knowledge of BI/Viz tools - Working knowledge of ELT/ETL tools (e.g., Fivetran, Airbyte) for batch use cases. - Working knowledge of data observability/reliability practices — automated alerting, lineage tracking.
Key Responsibilities - Model the business. Build and maintain clean, tested, documented dbt models in Snowflake, organized in clear staging, intermediate, and mart layers. - Partner with stakeholders. Work directly with teams across the company to understand what they're trying to accomplish, ask the questions behind the question, and steer requests toward something meaningful rather than just something requested.
- Strong SQL: fluent in CTEs and window functions, and able to untangle someone else's query. - Hands-on dbt and a cloud warehouse, ideally Snowflake, with a solid grasp of modeling patterns, testing, and documentation. - Python for data work and automation.
- - Airbyte or another ingestion/orchestration tool (ex: Airflow, Dagster) - Experience building a semantic layer (dbt Semantic Layer, Omni, LookML, or similar), especially one that serves both humans and AI agents. - Comfort with command line
- Python for data work and automation. - Experience with a modern BI tool (Metabase, Hex, Sigma, Omni, Looker or Tableau) and the speed to pick up the others. - Stakeholder fluency: you turn a vague ask into a defined problem, explain tradeoffs plainly, and push back when it helps.

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 28, 2026 · 2 days ago
Recorded sightings
2
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

🏆 Great Place to Work® Certified | USA

Harbor Compliance is a leading technology platform for entity compliance, helping more than 80,000 businesses and nonprofits manage licensing, tax registration, and legal entity requirements nationwide. Founded in 2012 and recognized repeatedly by the Inc. 5000 and Deloitte Technology Fast 500, we've grown through five strategic acquisitions — and are now backed by a 2026 majority growth investment from Bregal Sagemount to accelerate product, AI, and customer experience. We're a passionate team making compliance simpler and smarter for every organization we serve.

Harbor Compliance is launching its first company-wide data and analytics platform, pulling fragmented data from HubSpot, financial systems, and HRIS into one AI-augmented source of truth for a business that's scaling fast. Modern tools sit underneath and a shared metrics layer makes every number mean the same thing no matter who asks or which tool they ask in. As an Analytics Engineer, you'll join our Data Platform & Analytics team turning raw data into models, metrics, and dashboards the business leans on every day. You'll talk directly with stakeholders, pick up ambiguous problems and run with them, and have a real voice in how the team works.

Key Responsibilities

  • Model the business. Build and maintain clean, tested, documented dbt models in Snowflake, organized in clear staging, intermediate, and mart layers.
  • Partner with stakeholders. Work directly with teams across the company to understand what they're trying to accomplish, ask the questions behind the question, and steer requests toward something meaningful rather than just something requested.
  • Build the last mile. Create dashboards, explorations, and self-serve datasets in our BI tools so teams can answer their own questions with confidence.
  • Own metric and data governance. Define and maintain a shared set of metric definitions, document them, and resolve discrepancies when numbers don't match.
  • Keep the data trustworthy. Add tests, monitoring, and alerting so we find data issues before our stakeholders do, and help triage and fix them when they surface.
  • Work alongside data engineering. Collaborate on ingestion, warehouse performance, cost, and help define how raw data lands so downstream models stay reliable.
  • Ship like an engineer. Use Git, pull requests, code review, and CI to make changes safely and repeatedly.
  • Use AI to move faster. Apply AI tools in your daily workflow for writing and reviewing SQL, documentation, exploration, and debugging, and help the team figure out where AI genuinely helps and where it needs a human check.
  • Improve the program. Help define the best practices, standards, and documentation the team follows as we build out our analytics practice.

Requirements

  • 3–5 years in analytics engineering, data engineering, or a similar role.
  • Strong SQL: fluent in CTEs and window functions, and able to untangle someone else's query.
  • Hands-on dbt and a cloud warehouse, ideally Snowflake, with a solid grasp of modeling patterns, testing, and documentation.
  • Python for data work and automation.
  • Experience with a modern BI tool (Metabase, Hex, Sigma, Omni, Looker or Tableau) and the speed to pick up the others.
  • Stakeholder fluency: you turn a vague ask into a defined problem, explain tradeoffs plainly, and push back when it helps.
  • Genuine curiosity about how the business works, because understanding the why is how you build things that get used.
  • A working grasp of metric governance, data governance, and observability.
  • Git workflows on GitHub or GitLab.
  • AI in your daily workflow, with the judgment to verify what it gives you.
  • Appetite for a fast-moving company where you'll often build the process yourself.
  • Nice to haves:
    • Airbyte or another ingestion/orchestration tool (ex: Airflow, Dagster)
    • Experience building a semantic layer (dbt Semantic Layer, Omni, LookML, or similar), especially one that serves both humans and AI agents.
    • Comfort with command line

Skills and Knowledge

  • Fluency with SQL and working knowledge of dbt + lakehouse workflows
  • Working knowledge of BI/Viz tools
  • Working knowledge of ELT/ETL tools (e.g., Fivetran, Airbyte) for batch use cases.
  • Working knowledge of data observability/reliability practices — automated alerting, lineage tracking.
  • Fluency with AI-augmented development tools (e.g., Claude, Copilot) to accelerate engineering and documentation.

Accommodations:

Harbor Compliance is committed to providing any reasonable accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.


Compensation: 

Harbor Compliance’s base salary range for this role is listed below. Compensation at the time of offer is based on factors such as skill set, experience, qualifications, and work location. Salary is one part of Harbor Compliance’s total compensation package. Other benefits may include health benefits, flexible paid time off, parental leave, fertility and adoption assistance, 401(k), and educational reimbursement. Note that the salary range and benefits apply only to U.S.-based candidates.


Pay Transparency Policy Statement
Harbor Compliance will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by Harbor Compliance, or (c) consistent with Harbor Compliance’s legal duty to furnish information.


Equal Opportunity Statement

Harbor Compliance is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.


Notice Regarding the Use of Selection Technology

Harbor Compliance uses third-party automated tools and skills assessments (such as Testlify and Rippling) to help evaluate job applications and streamline our hiring workflow. These tools assist our recruitment team in reviewing qualification trends and scheduling, but all final employment decisions are made solely by humans on our Talent Success team, and all tools are subject to human oversight.

Depending on your location, local laws may grant you specific disclosure rights or the option to request an alternative evaluation process. If you require a reasonable accommodation or wish to opt out of automated assessment steps due to regional regulations, please notify your recruiter. Opting out will not negatively impact your application.


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