Analytics Engineer

We are seeking a highly skilled and proactive Analytics Engineer to join our dynamic Data & Analytics team. In this role, you will own data pipelines and reporting infrastructure - monitoring ETL, supporting Power BI operations, and building reliable datasets that the business depends on. You will leverage deep expertise in dbt, SQL, and Power BI, along with modern AI tooling, to keep our data accurate, fresh, and trusted across the organization, while helping advance the maturity of our data architecture and engineering practices.

You are a disciplined problem-solver who moves with urgency without sacrificing accuracy. You take ownership of the systems you support, ask strong questions, and bring order to complexity. You're comfortable working through ambiguity, improving systems over time, and holding your work to a high standard — because the data the business relies on depends on it.

Key Responsibilities:

• ETL Management (~35%): Own daily monitoring and troubleshooting of dbt and SQL Server / Redshift jobs, building automations to reduce manual effort over time. Efficiently identify root causes of failures and implement or oversee fixes, continuously improving the reliability and efficiency of ETL processes.
• Power BI Operations (~35%): Serve as the primary owner of the ETL processes supporting our core data mart, including proactively communicating issues and data freshness to stakeholders. Monitor daily reporting and semantic models, oversee the introduction of new fields, and identify and recommend solutions to architectural issues. Help manage and improve Power BI deployment pipelines. Contribute to report development in partnership with the broader team, supporting an evolution toward a "golden dataset" model (single source of truth) where SMEs build their own reports while core datasets remain closely held.
• Dataset Development (~20%): Build new and enhance existing datasets to expand our analytical capabilities, including data coming from internal/external APIs, ETL SaaS tools, Adhoc files, etc.
• Code Management (~10%): Use GitLab to provide thorough code review within our merge review process, identifying potential downstream impacts of changes — particularly to our data mart — and supporting our CI/CD pipeline.

Qualifications:

• 3 + years of experience in a data engineering, analytics engineering, or related technical data role and Bachelor's Degree in Computer Science, Data Science, Engineering, or a related field, or equivalent relevant experience.
• Advanced proficiency in dbt and SQL, including building scalable, modular data models with Jinja templating, macros, and incremental strategies, plus a strong grasp of query execution plans and performance optimization.
• Expert-level Power BI skills, including dataflows, Power Query, semantic models, DAX / measures, and report building.
• Demonstrated use of AI tools (e.g., for code generation, writing dbt tests, and debugging SQL) to improve speed and quality.
• Hands-on experience with AWS (S3, Redshift, IAM, etc).
• Familiarity with Git-based version control, code review workflows, and CI/CD pipelines using GitLab - including reading logs, understanding job triggers, and managing code deployments across dev, staging, and production environments.
• Working proficiency in Python for scripting, automation, and data manipulation - not a primary language for this role, but expected for day-to-day task automation and data handling. Strong problem-solving skills and the ability to quickly diagnose and resolve data issues with minimal direction.
• Excellent communication skills, with the ability to clearly convey data status, issues, and technical concepts to both technical and non-technical stakeholders.

Benefits:

• Competitive compensation
• 25 days of paid vacation
• Paid home and mobile internet
• 100% paid sick leave for up to 30 days a year
• Equipment for the Home Office
• English language classes
• Virtual and real team gatherings and activities
• Sports activities