Analytics Engineer

Havenpark Communities

. Design and implement facts and dimensions in dbt using staging, intermediate, core, and mart layers .

Posted 9/24/2026full-timeOrem • Utah • United StatesMid-LevelSenior💰 $100,000 - $140,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in dbt for data modeling, including the design and implementation of facts and dimensions, while ensuring data quality and performance through rigorous testing and documentation practices. Proficient in SQL and familiar with cloud data warehousing, particularly Snowflake, to support data-driven decision-making.

Highest-signal resume keywords

Strong SQL SkillsHands-On dbt ExperienceCloud Data Warehouse ExperienceGit/GitHub ProficiencyDimensional Modeling Fundamentals

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbtDimensional ModelingIncremental LogicData GrainTestingData QualityMetadata ManagementPythonAI Coding Tools

Soft Skills

Critical ReviewOwnershipDocumentation Habit

Tools & Technologies

SnowflakeGitGitHubFivetranCDataPower BISigma

Industry Keywords

Real EstateProperty ManagementFinanceOperations

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Design and implement facts and dimensions in dbt using staging, intermediate, core, and mart layers
Model slowly changing dimensions and mixed-grain snapshot sources
Make defensible grain and materialization decisions
Migrate legacy reports and business-critical views onto the new Core model
Reconcile report outputs line-for-line for trusted cutovers
Use AI coding tools for model development, test writing, and dbt/GitHub workflows
Review, correct, and own the correctness, performance, and style of AI-assisted work
Write dbt generic, singular, and unit tests
Establish contracts on data-out models and treat failing CI checks as release blockers
Integrate and document diverse source systems and their data-quality quirks
Curate mart models and metric definitions for governed self-service and agentic AI
Add metadata such as certification, PII level, and known issues
Follow small-PR, shared-style-guide, version-control, and documentation practices

Requirements

What you’ll need

Strong SQL skills, including window functions, deduplication, incremental logic, and data grain
Ability to critically review and correct AI-generated SQL and take ownership of results
Hands-on dbt experience with models, tests, macros, refs/sources, and layered project structure
Experience with a cloud data warehouse, ideally Snowflake
Comfortable with Git/GitHub and PR-based, review-driven workflows
Dimensional modeling fundamentals, including facts, dimensions, and slowly changing dimensions
Habit of documentation and testing
AI coding assistant experience preferred
ELT tooling experience with Fivetran or CData preferred
Semantic or metrics layer experience, or preparing data for AI/LLM consumers preferred
BI tooling experience such as Power BI or Sigma preferred
Domain exposure to real estate, property management, finance/GL, or operations preferred
Python for ancillary tooling and automation preferred

Benefits

Comp & perks

Greenfield platform with modern tooling, code review, and CI from day one
AI coding tools to accelerate development
Work that directly drives operational and capital-allocation decisions
Craft-focused engineering culture valuing small diffs, clean models, and good tests