Analytics Engineer

Harbor Compliance

10h•$93,800 - $117,300

About The Position

Harbor Compliance is building its first company-wide data and analytics platform, consolidating fragmented data from systems such as HubSpot, financial systems, and HRIS into an AI-augmented source of truth. The Analytics Engineer will join the Data Platform & Analytics team to turn raw data into reliable models, metrics, and dashboards used across the business. The role involves direct stakeholder partnership, independently working through ambiguous problems, and helping shape the team's practices and analytics platform. The engineer will build and maintain tested, documented dbt models in Snowflake; create dashboards and self-service datasets; define shared metrics and governance practices; and implement data quality tests, monitoring, and alerting. They will collaborate with data engineering on ingestion, warehouse performance and cost, use Git-based workflows and CI, apply AI tools in daily development with appropriate verification, and help establish standards and documentation for the analytics practice.

Requirements

3–5 years of experience in analytics engineering, data engineering, or a similar role.
Strong SQL skills, including fluency with CTEs and window functions and the ability to understand and untangle existing queries.
Hands-on experience with dbt and a cloud data warehouse, ideally Snowflake, and a solid grasp of modeling patterns, testing, and documentation.
Python skills for data work and automation.
Experience with a modern BI tool such as Metabase, Hex, Sigma, Omni, Looker, or Tableau, and ability to learn other tools quickly.
Ability to translate vague stakeholder requests into defined problems, explain tradeoffs clearly, and push back when appropriate.
Curiosity about how the business works and the ability to understand the purpose behind requests.
Working knowledge of metric governance, data governance, and observability.
Experience with Git workflows on GitHub or GitLab.
Use of AI in daily work, with judgment to verify its outputs.
Willingness to work in a fast-moving company and build processes as needed.

Nice To Haves

Experience with Airbyte or another ingestion or orchestration tool, such as Airflow or Dagster.
Experience building a semantic layer, such as dbt Semantic Layer, Omni, LookML, or similar, especially one serving both people and AI agents.
Comfort with the command line.

Responsibilities

Build and maintain clean, tested, documented dbt models in Snowflake, organized into staging, intermediate, and mart layers.
Partner with stakeholders across the company to clarify goals, define meaningful problems, and guide requests toward useful solutions.
Create dashboards, explorations, and self-service datasets in BI tools.
Define, document, and maintain shared metric definitions and resolve discrepancies in reported numbers.
Add data tests, monitoring, and alerting; triage and fix data issues when they arise.
Collaborate with data engineering on ingestion, warehouse performance and cost, and how raw data is landed.
Use Git, pull requests, code review, and CI to deliver changes safely and consistently.
Use AI tools for SQL, documentation, exploration, and debugging, and help determine where AI is useful and where human review is needed.
Help establish analytics best practices, standards, and documentation.