Job Title: Data and Analytics Engineer
Location Requirements: Onsite
Job Type: Direct Hire
Role Overview:
You will take charge of designing and maintaining end-to-end data pipelines using a set stack that includes Snowflake, Airflow, dbt, Python, and Power BI. This engineering-first role emphasizes ownership of modeling, performance tuning, and semantic layers, with heavy AI-assisted workflows. The culture values low bureaucracy, high autonomy, and problem solvers who are humble and scrappy.
Responsibilities:
Build and optimize data pipelines leveraging Snowflake and Airflow
Develop and maintain Snowflake data models and ensure performance tuning
Create and manage production data workflows using Airflow, including monitoring, retries, and dependency management
Develop data models and transformations with dbt, including tests and documentation
Collaborate on source models, exposure documentation, and CI checks
Build semantic models in Power BI, including DAX measures, refresh, and stakeholder engagement
Use AI tools such as Claude, Copilot, Cursor, and VS Code to generate, review, test, and refine code, ensuring guardrails are followed
Own the full pipeline lifecycle and deliver end-to-end solutions
Required Qualifications:
Hands-on experience with Snowflake and Airflow in a real work environment
Proficiency in Python and SQL for production pipelines
Experience with dbt, including writing tests, documentation, and structuring models
Familiarity with Git/GitHub pull request workflows, branching, and reviews
Knowledge of AI-first workflows using Claude, Copilot, Cursor, and VS Code
Strong problem-solving skills, curiosity, and a gritty mindset
Ability to work autonomously on vague goals and define deliverables independently

Data and Analytics Engineer

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