Senior Data Systems Analyst

Recrute Action•Markham, ON

2d•CA$85 - CA$110•Hybrid

About The Position

Support large-scale enterprise data initiatives within a fast-evolving insurance environment focused on analytics, ETL, SQL, and modern data platforms. This hybrid role offers the opportunity to work on high-impact digital transformation projects, collaborate with experienced technical and business teams, and contribute to advanced data solutions driving business performance and innovation.

Requirements

University degree in Computer Engineering or Computer Science.
5 years of experience leading Data Systems Analysis organizations with expertise in large-scale enterprise data assets.
8 years of experience as a Business Analyst on mid-to-large-scale projects involving enterprise data systems design, development, and implementation.
Strong data analysis skills with advanced SQL expertise.
Strong ETL and data engineering background.
Experience working in data warehouse and data lake environments.
Solid experience with data technologies and tools including Snowflake, Hadoop, PostgreSQL, and Informatica.
Outstanding knowledge and hands-on experience with ETL processes using the Informatica product suite.
Experience establishing documentation standards and frameworks for data quality, governance, stewardship, and metadata management.
Strong understanding of complex business processes supporting technical systems.
Strong leadership and influencing skills with senior management stakeholders.
Strong analytical, critical thinking, and problem-solving skills.
Strong stakeholder management skills.
Solid understanding of project and program management processes.
Excellent verbal and written communication skills.

Nice To Haves

Insurance industry knowledge is considered an asset.

Responsibilities

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.
Segment customers based on behavior, risk profiles, and product usage.
Analyze customer lifetime value, churn risk, and cross-sell and up-sell opportunities.
Collaborate with risk and compliance teams to monitor exposure and regulatory thresholds.
Prepare data extracts and reports for regulatory bodies.
Ensure data lineage and traceability for audit and compliance purposes.
Validate data accuracy and completeness for filings and disclosures.
Clean and transform raw data from diverse sources into analytics-ready formats.
Leverage lakehouse tools to manage versioned and time-travel datasets.
Collaborate with data engineers to support ETL and ELT processes.
Build dashboards and visualizations for underwriting, claims, finance, and product teams.
Present insights using business intelligence and visualization tools.
Enable self-service analytics through reusable datasets and semantic layers.
Profile and validate data to ensure consistency across policy, claims, and financial domains.
Support metadata management, data governance, stewardship, and master data initiatives.
Work closely with actuaries, underwriters, product managers, and IT teams to understand business data needs.
Translate business requirements into analytical queries and data models.
Document business logic, assumptions, and data definitions.
Assist data scientists with feature engineering and exploratory data analysis.
Provide historical data extracts for model training and validation.
Interpret analytical model outputs and integrate findings into business reporting.
Lead data systems analysis activities supporting enterprise-scale data assets and analytics capabilities.