Analytics Engineer

Havenpark Communities is building a greenfield analytics platform and needs an Analytics Engineer to own the transformation layer. This role will turn operational, messy data into trusted facts and dimensions in Snowflake using dbt, with a governed semantic layer that enables reliable self-service and agentic AI questions.

Responsibilities

• Design and implement facts and dimensions in dbt using a disciplined staging → intermediate → core → mart architecture.
• Model slowly changing dimensions, support mixed-grain snapshot sources, and make defensible decisions about grain and materialization.
• Reconstruct existing business-critical views and reports on top of the new model, reconciling outputs line-for-line to support stakeholder confidence during cutover.
• Use AI coding tools to accelerate dbt model development, test writing, and the dbt/GitHub workflow, while reviewing outputs for correctness, performance, and style and taking full ownership to fix issues.
• Write dbt tests including generic, singular, and unit tests; establish contracts on data-out models; treat failing CI checks as a release blocker.
• Work with data from multiple sources, each with distinct quirks, grains, and coverage gaps, and document findings.
• Curate mart models and metric definitions with metadata such as certification, PII level, and known issues to power governed self-service and agentic AI use cases for non-analysts.
• Elevate engineering practice through small, reviewable PRs, a shared style guide, version control as the source of truth, and documentation that an engineer or AI agent can use.

Requirements

• Strong SQL skills, including the ability to read, write, and evaluate queries involving window functions, deduplication, incremental logic, and grain.
• Judgment to work with AI tooling rather than be replaced by it, including the ability to detect subtly incorrect generated SQL and own corrections.
• Hands-on dbt experience (Core or Cloud), including models, tests, macros, refs/sources, and familiarity with layered project structure.
• Experience with a cloud data warehouse, ideally Snowflake.
• Comfort with Git/GitHub and a PR-based, review-driven workflow.
• Dimensional modeling fundamentals, including facts, dimensions, and SCDs, plus the ability to avoid over-engineering.
• Strong documentation and testing habits that make work legible and verifiable.

Technologies

• Snowflake
• dbt
• SQL
• Git
• GitHub
• CI
• Power BI
• Sigma
• Fivetran
• CData
• Claude Code
• Copilot
• Cursor
• Python

Benefits

• Greenfield work with guardrails.
• AI-accelerated development with human ownership.
• Your work ships decisions.
• Craft is valued.

Nice-to-Haves

• Experience using AI coding assistants (for example, Claude Code, Copilot, Cursor) in a professional, review-gated workflow.
• ELT tooling experience, including Fivetran and CData, and experience taming third-party source schemas.
• Semantic layer/metrics layer experience, or experience preparing data for AI/LLM consumers.
• BI tooling experience (for example, Power BI or Sigma), including partnering directly with report consumers.
• Domain exposure to real estate, property management, finance/GL, or operations.
• Python for ancillary tooling and automation.

How We Work Matters

The team leverages AI heavily across the development workflow, including authoring and refactoring SQL, building dbt models, writing tests, and moving work through a GitHub PR process. AI acts as a force multiplier rather than a crutch or black box. The engineer fully owns what ships under their name, reading and understanding changes in review, catching model mistakes, and standing behind the result.

Use of Artificial Intelligence in Hiring

Havenpark Communities may use artificial intelligence tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals based on available information. These tools assist the recruitment team and do not replace human judgment. Final hiring decisions are ultimately made by humans.