Associate, Analytics Engineer
About The Position
Our Analytics Engineer turns raw, multi-source data into trusted, well-modelled datasets that the whole business can use. Sitting between Data Engineering and Analytics, this role owns the transformation layer: the models, tests, and documentation that feed reporting, BI, and AI across Investments, Portfolio, Operations and Finance. This is a hands-on, high-leverage role, building the curated, source-of-truth foundation that lets Perform automate reporting, cut the coordination tax between systems, and shorten the time-to-Insight for decision-makers. This role reports to the Vice President, Data & Analytics and is based in the office, 5 days a week.
Requirements
- 5+ years building data models and pipelines in an analytics engineering, data engineering and/or BI engineering role
- Advanced proficiency in SQL and DBT (or a comparable transformation and testing framework)
- Demonstrable success working with modern data warehouses (Databricks, Snowflake, BigQuery, RedShift)
- Experience with cloud infrastructure (Azure, AWS, or GCP)
- Experience with cloud-hosted data visualization tooling
- Working knowledge of dimensional modelling, curated / medallion-layer design, Git and CI/CD for analytics
- Demonstrable ability to translate business questions into durable data models with agreed metric definitions
- Strong requirements-gathering and stakeholder-management skills
Nice To Haves
- Advanced proficiency in Azure Platform as a Service
- Proficiency in common data engineering tools (Apache Airflow, Azure Data Factory)
- Advanced proficiency in common visualization tools (Tableau, PowerBI)
- Bachelor's Degree in Computer Science, Mathematics, Analytics, or relevant tertiary education
Responsibilities
- Build data transformation layers that deliver clean, unambiguous, stakeholder-ready information to our data warehouse
- Shift measurement decisions from ad-hoc queries and BI tools to flexible silver and gold data layers
- Enable recurring, exploratory, and self-service reporting capabilities, driving stakeholders to make faster, better-informed decisions in their daily work
- Ensure data quality via documented lineage, automated checks, and clear definitions, making our results trustworthy by default
- Support data governance & stakeholder engagement, encouraging accuracy in interpretation
- Model the successful use of AI as a capability, leveraging data model outputs via MCPs, and balancing AI tooling efficiencies with domain expertise
Benefits
- health insurance coverage
- retirement savings plan
- paid holidays
- paid time off (PTO)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
