Data Business Analyst

Data Business Analyst (Insurance Analytics & Informatica/Snowflake)

Location:

Markham, Ontario

• Claims Policy Data Analysis – Analyze structured and semi-structured data related to claims, policies, underwriting, and customer interactions. Identify patterns in claims frequency, fraud indicators, and loss ratios using lakehouse datasets. Support actuarial teams with data extracts and trend analysis.
• Customer Risk Insights – Segment customers based on behavior, risk profiles, and product usage. Analyze customer lifetime value, churn risk, and cross-sell/up-sell opportunities. Collaborate with risk and compliance teams to monitor exposure and regulatory thresholds.
• Regulatory Compliance Reporting – Prepare data extracts and reports for regulatory bodies (e.g., OSFI, FSRA, NAIC). Ensure data lineage and traceability for audit and compliance purposes. Validate data accuracy and completeness for filings and disclosures.
• Data Wrangling Preparation – Clean and transform raw data from diverse sources (policy admin systems, CRM, claims systems) into analytics‑ready formats. Leverage lakehouse tools (Delta Lake, Apache Iceberg) to manage versioned and time‑travel datasets. Collaborate with data engineers to ensure efficient ELT processes.
• Business Intelligence Visualization – Build dashboards and visualizations for underwriting, claims, finance, and product teams. Use tools like Power BI, Tableau, or Qlik to present insights from lakehouse data. Enable self‑service analytics by creating reusable datasets and semantic layers.
• Data Quality Governance – Profile and validate data to ensure consistency across policy, claims, and financial domains. Tag and catalog datasets using metadata tools (Unity Catalog, Collibra). Support master data management and reference data initiatives.
• Collaboration – Stakeholder Engagement:
  Work with actuaries, underwriters, product managers, and IT teams to understand data needs. Translate business questions into analytical queries and data models. Document business logic, assumptions, and data definitions clearly.
• Predictive Advanced Analytics – Support data scientists with feature engineering and exploratory data analysis. Provide historical data extracts for model training and validation. Interpret model outputs and integrate them into business reporting.

• University degree in Computer Engineering or Computer Science.
• Minimum 5 years of experience leading Data Systems Analysis organizations with expertise in building large‑scale enterprise data assets.
• 8 years experience as a Business Analyst working on mid‑large projects for data design, development, and implementation of business‑critical enterprise data systems.
• Solid grasp of data technologies/tools (Snowflake, Hadoop, Postgre
  
  SQL, Informatica, etc.). Outstanding knowledge and experience in ETL with Informatica product suite.