Data Analytics Engineer

Responsibilities:

The following information is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all duties, responsibilities, or required skills.

• 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. Run requirements gathering with stakeholders. Establish the grain, surface the edge cases, write down the business rules, and push back when the 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. Write table and column documentation that traces each field to its true origin. This documentation is consumed by AI agents as well as humans, and is an integral part of the semantic layer.
• Diagnose and resolve data incidents.
• Review your 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.
• Help make the team faster. Improve the agent playbooks, documentation, and tooling the team uses to work with the warehouse.

Qualifications and Job Requirements:

• 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. You already use tools such as Claude Code, Cursor or equivalent as part of your daily working practice. You know 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). You understand dependency graphs, refs, incremental strategies, tests and environment promotion as concepts, not just as commands.
• Git fluency. Branching, pull requests, code review, conflict resolution and generally working with a critical production environment.
• Strong familiarity with orchestration tools such as Airflow, Cloud Composer, Dagster or Prefect. You can read a DAG, understand its schedule and dependencies, and find out why a task failed.
• Process discipline. Jira, ticket hygiene, and code review etiquette. It’s mandatory you understand how to avoid shipping unverified LLM-generated code.
• Experience in doing 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.
• Familiarity with BI tools (Tableau, Power BI, etc.).
• Detail oriented, methodical, and thorough.
• Team player who builds strong relationships and collaborates with others.
• 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; take ownership of quality, accuracy, and timeliness of deliverables.
• You must be a world-class individual contributor to thrive at Toptal. You will not be here just to tell other people what to do.