Data Analytics Engineer in Vancouver

Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams, on-demand. With $200+ million in annual revenue and team members based around the globe, Toptal is the world’s largest fully remote workforce. We take the best elements of virtual teams and combine them with a support structure that encourages innovation, social interaction, and fun.

Our Data Analytics Engineers focus on creating a data environment that is conducive to analytics and business decision making. You will own and maintain the data transformation layer. This will require:

• Data governance (quality, accuracy, coverage, security)
• Data modeling (structure, relationships, integrity)
• Technical communication (data dictionaries, user training)
• Quality control (code reviews, data validation)
• Raw data analysis
• Building AI data systems and pipelines

You will be the product owner for our data warehouse and will coordinate closely with our functional Business Analysts on one side, and Data Engineers on the other. This role sits within the Business Analytics Center of Excellence and will ensure trustworthy data is available for all downstream data users. Positive relationships with both Data Engineers and Business Analysts will be key, but you must also think independently and bring your own point of view.

To be successful in this role you must live and breathe SQL daily and be a critical thinker, problem solver and self-starter. This role requires an AI-heavy workflow and skillset. Fluency with using LLMs and agentic coding tools is a requirement of this role.

Responsibilities:

• 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.
• 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.
• Experience with cloud data warehousing, such as BigQuery or Snowflake.
• Good understanding of a modern transformation framework (dbt, Dataform, SQLMesh or similar).
• Git fluency.
• Strong familiarity with orchestration tools such as Airflow, Cloud Composer, Dagster or Prefect.
• Process discipline.
• 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.