Analytics Engineer, BI Modernization
Job Description & How to Apply Below
We are seeking an Analytics Engineer to support the modernization of legacy reporting and analytics capabilities into a governed, cloud-based architecture. This is a hands-on, SQL-heavy role focused on analytical data modeling, semantic layers, data quality, and BI modernization.
Key Responsibilities- Develop complex SQL queries, views, and reusable analytical datasets.
- Build and maintain analytical, dimensional, and semantic data models.
- Translate business and reporting requirements into scalable, governed data solutions.
- Optimize SQL and analytical models for performance, scalability, and reuse.
- Develop shared metrics, calculations, business rules, and semantic models.
- Support migration and modernization of legacy BI, reporting, and analytics platforms.
- Analyze legacy reports, SQL, workflows, calculations, and data dependencies as needed.
- Simplify and consolidate duplicated legacy logic into reusable modern solutions.
- Validate modernized outputs and investigate data or business-rule discrepancies.
- Apply Git, version control, peer review, documentation, testing, and controlled deployment practices.
- Collaborate with BI, analytics, data engineering, and business teams.
- 5+ years of experience in Analytics Engineering, BI Engineering, Data Engineering, or a related field.
- Strong experience developing complex SQL queries, views, and reusable datasets.
- Experience with dimensional and analytical data modeling, including facts, dimensions, grain, measures, and relationships.
- Experience with relational databases and cloud-based analytical platforms.
- Experience with BI modernization, reporting migration, or legacy platform transformation.
- Strong analytical, troubleshooting, validation, documentation, and communication skills.
- Expert-level SQL, including complex joins, CTEs, window functions, aggregations, and query optimization.
- Strong analytical, dimensional, and semantic modeling skills.
- Experience with cloud data platforms;
GCP/Big Query preferred. - Experience with semantic or metrics layers such as Cube, dbt Semantic Layer, LookML, or similar technologies preferred.
- Experience with BI tools such as Cognos, Alteryx, Tableau, or Power BI is an asset.
- Proficiency with Git/version control and modern development practices.
- Experience using AI-assisted development tools for SQL, coding, documentation, analysis, or troubleshooting is preferred.
Bachelor’s degree in Computer Science, Information Systems, Data, Analytics, Engineering, or a related field preferred. Equivalent professional experience will be considered.
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