Description:
As part of our ongoing and ambitious Digital Transformation initiative, we anticipate that additional hours may occasionally be required beyond the standard work week to meet critical milestones and deliverables. We kindly ask that all candidates you put forward meet the following criteria: On-site availability: Must be able to work from our Markham office a minimum of three days per week.
Flexibility: Must be willing and able to work extended hours when necessary to support project needs.
Working with us offers a unique opportunity to contribute to high-impact, forward-looking initiatives in a collaborative and innovative environment. All our team members benefit from opportunities to work alongside experienced leaders and cross-functional teams driving meaningful change. We appreciate your partnership in identifying candidates who are not only technically qualified but also aligned with our commitment to excellence and transformation. We are seeking a collaborative and resourceful Data Systems Analyst for our fast-paced candidate. You will be leading the data systems
analysis team and help scale the data and analytics capabilities. You will be responsible for
being a liaison between various business units and technical data teams. You'll be required
to apply your depth of knowledge and expertise to all areas including requirements,
documentation, road mapping, data analysis, and data analytics. Further, you will be part of
the data transformation initiatives to help build the right data mindset to enable our
direct-to-consumer business, data science capabilities, and expand our digital footprint.
This role will be part of and a member of our Information Technology Data Delivery Group.
You will be responsible for creating the center of excellence for the data ecosystem artifacts
creation, maintenance, and project requirements in a high-performing, and experienced
team. You'll be required to apply your depth of knowledge and expertise to all many areas
including requirements, infrastructure, and solution documentations.
on an exciting journey to modernize, craft, and build a next generation of data platform to
support the growing data needs for data engineering, analytics, and Data Science.
We embrace a culture challenging the status quo and constantly look to efficiently simplify
processes, technology, and workflow. 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. |