Data Analytics Engineer

Overview

Own and maintain the data transformation layer and act as product owner for the data warehouse, laying the data foundation for the Business Analytics Center of Excellence. This is a remote position.

What you'll do

• Design, write, review and ship SQL models across our repositories that transform raw data into usable data products for all organizational stakeholders.
• Own and maintain the transformation layer.
• Proactively work with the Data Engineers to ensure new data sources are added and available, and then modeled and published in our data warehouse.
• Proactively monitor the data warehouse and extract insights to identify opportunities to improve data operations, data accuracy and quality, coverage, integrity, structure, and general usability.
• Turn ambiguous business asks into modeled data, running requirements gathering with stakeholders, establishing the grain, surfacing edge cases, writing down business rules, and pushing back when a request would produce a misleading number.
• Implement measures and processes to improve data quality, accuracy, coverage, lineage, access and retention across dozens of source production databases.
• Own the data dictionary, writing table and column documentation that traces each field to its true origin.
• Diagnose and resolve data incidents.
• Review teammates' code and provide feedback to maintain the hygiene of the data warehouse production environment.
• Work closely with Business Analysts, Data Engineers, Data Scientists, and business process owners to empower data-driven decision making.
• Enable end users to better use data, understand complexities, nuances, and limitations.
• Improve the agent playbooks, documentation, and tooling the team uses to work with the warehouse.

What you'll need

• Bachelor's degree is required, preferably in Engineering or a related technical field.
• 4+ years of experience in an Analytics Engineer, Data Engineer, or Data Analyst role where you personally shipped production data models.
• Expert-level SQL skills and a working knowledge of Python.
• Fluency with LLMs and agentic coding tools, such as Claude Code, Cursor or equivalent, including knowing where they are reliable, where they should not be used, and how to verify their output.
• Experience with cloud data warehousing, such as BigQuery or Snowflake.
• Good understanding of a modern transformation framework (dbt, Dataform, SQLMesh or similar), including dependency graphs, refs, incremental strategies, tests and environment promotion as concepts.
• Git fluency, including branching, pull requests, code review, conflict resolution and working with a critical production environment.
• Strong familiarity with orchestration tools such as Airflow, Cloud Composer, Dagster or Prefect, including reading a DAG, understanding its schedule and dependencies, and finding out why a task failed.
• Process discipline, including Jira, ticket hygiene, and code review etiquette, and understanding how to avoid shipping unverified LLM-generated code.
• Experience in exploratory/raw data analysis, data modeling, and data governance (quality, accuracy, coverage, security, etc.).
• Experience translating business logic and objectives into SQL code and linking data and analytics to business strategy and operations to drive real impact.
• Detail oriented, methodical, and thorough.
• Outstanding written and verbal communication skills, including the ability to explain complex issues in a simple and intuitive way.
• Ability to work collaboratively and independently, taking ownership of quality, accuracy, and timeliness of deliverables.

Nice to have

• Familiarity with BI tools (Tableau, Power BI, etc.).

Details

• Remote position.
• No visa sponsorship or assistance is offered.
• Resumes and communication must be submitted in English.