Remote Insurance Data Analytics Jobs in Toronto, ON

Capco is looking for a Consultant, Data Engineer to join our Technology & Engineering practice in Toronto. This is an exciting opportunity for an analytical professional who enjoys solving complex data challenges, validating large datasets, and delivering high-quality insights for leading financial services clients.

Working alongside multidisciplinary teams, you will help ensure the integrity, accuracy, and consistency of critical business data, enabling successful technology delivery and informed decision-making.

The Data Engineer will have strong Python, Pandas, and NumPy expertise to support data validation, reconciliation, and processing of large datasets. This role focuses on comparing multiple datasets, identifying data quality issues, automating data validation workflows, and supporting analytics initiatives. This is a hands-on engineering role with a strong emphasis on Python-based data processing and data quality management.

Programming & Data Processing

• Python (3+ years of hands-on experience)
• Pandas (Advanced)
• NumPy (Advanced)
• SQL

Data Engineering & Analytics

• Experience processing and validating large datasets (millions of records)
• Data reconciliation and dataset comparison
• Data cleansing and transformation
• Data quality analysis and validation
• ETL/Data Pipeline fundamentals
• Root cause analysis of data discrepancies

Key Responsibilities

• Validate and reconcile two or more datasets simultaneously.
• Build Python-based data validation and comparison frameworks.
• Use Pandas and NumPy extensively to analyze, transform, and validate large datasets.
• Develop automated processes to identify missing, duplicate, or inconsistent data.
• Investigate data quality issues and determine root causes.
• Create reports highlighting discrepancies and data quality metrics.
• Collaborate with business, analytics, and engineering teams to resolve data issues.
• Optimize large-scale data processing workflows.

Experience Required

• 3-5+ years of experience in Data Engineering, Data Analytics, or Data Quality Engineering.
• Strong hands-on experience with:

• Python
• Pandas
• NumPy
• SQL

• Experience working with large structured datasets.
• Experience comparing and reconciling data from multiple sources.

Day-to-Day Activities

• Receive data extracts from multiple systems.
• Load and process large datasets using Python, Pandas, and NumPy.
• Compare datasets to identify gaps, inconsistencies, and anomalies.
• Build validation rules and automated quality checks.
• Investigate data issues and communicate findings to stakeholders.
• Create reusable scripts and frameworks for ongoing validation activities.
• Support data migration, onboarding, and integration projects.

Nice to Have

• PySpark
• Azure Data Factory
• Databricks
• Power BI
• Git
• CI/CD
• Cloud platforms (Azure, AWS, GCP)

Ideal Candidate

A hands-on Data Engineer with strong Python, Pandas, and NumPy expertise who can efficiently validate, reconcile, and analyze multiple large datasets while building automated solutions to improve data quality and consistency.

• Deliver high-impact technology solutions for Tier 1 financial institutions.
• Work in a collaborative, flat, and entrepreneurial consulting culture.
• Access continuous learning, training, and industry certifications.
• Be part of a team shaping the future of digital financial services.
• Help shape the future of digital transformation across financial services.

• Comprehensive Benefits Coverage - 100% company-paid health, life, and disability insurance effective from Day 1 of employment.
• Retirement Savings Program - Registered Retirement Savings Plan (RRSP) with the option of receiving a matching employer contribution.
• Virtual Health Care - Company-paid program available to all employees and their dependents/partners.
• Employee & Family Assistance Program (EFAP) - Company-paid support services for employees and their dependents/partners.
• Additional support including enhanced parental leave, wellness reimbursement, a Business Coach from Day 1, and other employee wellbeing benefits.

We're committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know-we'll be happy to help. We value each person's unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration-a mindset that shapes how we work with clients and each other every day.

At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

We are currently hiring for this role due to an existing or newly created vacancy within our organization. This position is open as part of our ongoing business needs, and we are actively reviewing applications to fill this role with a qualified candidate who can make an immediate impact.