Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and sustain organized, tested, and well-documented dbt models within Snowflake across staging, intermediate, and mart layers.

• Collaborate closely with stakeholders to comprehend objectives, clarify ambiguous challenges, and create impactful solutions.

• Design dashboards, exploratory analyses, and self-service datasets utilizing BI tools.

• Define, document, and uphold shared metric definitions.

• Address discrepancies when metrics do not align.

• Implement data tests, monitoring, and alerting systems.

• Diagnose and resolve data-related issues.

• Partner with data engineering on data ingestion, warehouse efficiency, cost management, and raw-data landing practices.

• Utilize Git, pull requests, code review, and CI to deploy changes securely.

• Leverage AI tools to enhance SQL, documentation, exploration, and debugging workflows.

• Contribute to the establishment of best practices, standards, and documentation for the analytics function.

⛳️ Requirements

• 3–5 years of experience in analytics engineering, data engineering, or a related role.

• Proficiency in SQL, including Common Table Expressions (CTEs) and window functions.

• Practical experience with dbt and a cloud data warehouse, preferably Snowflake.

• Strong understanding of modeling patterns, testing methodologies, and documentation practices.

• Proficient in Python for data-related tasks and automation.

• Familiarity with modern BI tools such as Metabase, Hex, Sigma, Omni, Looker, or Tableau.

• Ability to convert vague stakeholder requests into clearly defined problems and articulate trade-offs.

• Working knowledge of metric governance, data governance, and observability concepts.

• Experience with Git workflows on platforms like GitHub or GitLab.

• Incorporation of AI in daily tasks, with the discernment to validate outputs.

• Willingness to thrive in a fast-paced environment where processes may need to be independently developed.

• Proficient in SQL and a working understanding of dbt and lakehouse workflows.

• Familiarity with BI/Visualization tools.

• Knowledge of ELT/ETL tools such as Fivetran or Airbyte for batch processing.

• Understanding of data observability and reliability practices, including automated alerting and lineage tracking.

• Proficiency with AI-enhanced development tools like Claude or Copilot.

• Nice to have: Experience with Airbyte or other ingestion/orchestration tools like Airflow or Dagster.

• Nice to have: Experience in building a semantic layer such as dbt Semantic Layer, Omni, or LookML.

• Nice to have: Comfort with command line operations.

🏝️ Benefits

• Health benefits.

• Flexible paid time off.

• Parental leave.

• Fertility and adoption assistance.

• 401(k) plan.

• Educational reimbursement.

• Reasonable accommodations during the application and interview process.

• Human oversight of automated assessment tools.

• Option to request an alternative evaluation process or opt out of automated assessment steps, depending on location.