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.
Required Qualifications
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.
Technical 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/BigQuery 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.
Education
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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