Data & Analytics Engineer building scalable data platforms for Ledgebrook, an insurance company. Designing pipelines, governance, and cloud data systems while partnering with technical and insurance teams.
About the role
- Data Engineer building dbt models, pipelines, and quality systems for Financeit’s Canadian point-of-sale financing platform. Supporting analytics, reporting, governance, and data migrations.
Responsibilities
- Collaborate with high-visibility teams and stakeholders to support critical data engineering initiatives
- Build and maintain dbt models across staging, mart, and metrics layers in the data warehouse
- Support analytics, reporting, and business intelligence tools
- Define and enforce data quality standards, best practices, and data governance policies with cross-functional teams
- Improve data discoverability and maintain data documentation
- Help data consumers find and use required data
- Monitor data pipeline health and investigate data quality issues
- Assess the impact of data quality issues and validate fixes with business stakeholders
- Develop and maintain data and automation scripts for data testing and efficiency
- Participate in data migration projects and ensure data quality and integrity
- Stay current with data quality tools and emerging data engineering technologies
- Contribute to process improvements, documentation, and knowledge sharing within the data team
- Foster a team culture of passion, curiosity, and continuous improvement
Requirements
- University degree in Engineering, Math, or Computer Science
- 2+ years of full-time and/or internship/PEY experience as a Data Engineer or Data Analyst
- Strong hands-on SQL experience
- Ideally dbt experience, including layered data models, macros, and incremental materializations
- Python proficiency for pipeline development, data transformation, and scripting automation
- Experience with Apache Airflow, including building and debugging DAGs, managing task dependencies, and handling production failures
- Familiarity with AWS services, particularly Redshift and Glue
- Comfort working in a cloud data warehouse environment
- Experience working in indirect (B2B2C) and/or consumer lending is a strong asset
- Good working knowledge of agile delivery techniques
- Strong data modeling knowledge, including staging, fact, and dimension tables
- Ability to manage competing priorities while meeting deadlines
- Ability to follow and manage best practices and standards for data quality, scalability, reliability, and reusability
- Successful background and credit check, among other verifications, as a condition of employment
Benefits
- Competitive pay
- Performance-based bonus: Annual Bonus: 20%
- Flexible work arrangements
- Hybrid workplace options
- Comprehensive medical coverage
- Dental coverage
- Vision coverage
- Lifestyle Account
- RRSP Matching
- Parental Leave Top UP Program
- In office massage
- Meditation sessions
- Workout sessions
- Virtual Lunch & Learns
- Company parties
- Fun team activities
- Charity initiatives
- Career learning and development programs
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