Data System Analyst
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**Job Title: Data System Analyst**
**Location: Markham, ON****Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed))** **Job Type: Full time CAD120K**
**What you’ll do** 1\. 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.
2\. 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.
3\. 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.
4\. Data Wrangling \& Preparation* Clean and transform raw data from diverse sources (e.g., policy admin systems, CRM, claims systems) into analytics\-ready formats. * Leverage lakehouse tools (e.g., Delta Lake, Apache Iceberg) to manage versioned and time\-travel datasets. * Collaborate with data engineers to ensure efficient ETL/ELT processes.
5\. 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.
6\. Data Quality \& Governance* Profile and validate data to ensure consistency across policy, claims, and financial domains. * Tag and catalog datasets using metadata tools (e.g., Unity Catalog, Collibra). * Support master data management and reference data initiatives.
7\. 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.
8\. Predictive \& Advanced Analytics Support* Assist 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.
**What you’ll bring*** University degree in Computer Engineering or Computer Science. * Minimum 5 years’ of experience successfully 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/experience with data technologies \& tools (Snowflake, Hadoop, PostgreSQL, Informatica, etc.,) * Outstanding knowledge and experience in ETL with Informatica product suite. * Experience establishing documentation standards frameworks for data quality, data governance, stewardship and metadata management. * Ability to foundationally understand complex business process driving technical systems. * Strong leadership and influencing skills at the senior management level. * Strong analytical, critical thinking and problem\-solving skills. * Strong stakeholder management. * Solid understanding of Project and Program Management processes. * Excellent verbal and written communication skills. * Insurance knowledge an asset
### **Requirements**
**Job Title: Data System Analyst**
**Location: Markham, ON****Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed))** **Job Type: Full time CAD120K**
**What you’ll do** 1\. 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.
2\. 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.
3\. 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.
4\. Data Wrangling \& Preparation* Clean and transform raw data from diverse sources (e.g., policy admin systems, CRM, claims systems) into analytics\-ready formats.
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