Data Engineer

Tokio Marine Canada Ltd • Toronto, ON

33d • CA$80,000 - CA$100,000 • Hybrid

About The Position

Tokio Marine Canada (TMCan) is a Canadian early-stage entrepreneurial commercial P&C insurer based in Toronto. We partner with select brokers to deliver tailored business insurance solutions across Canada. As part of the Tokio Marine Group, we are able to collaborate under a shared framework while maintaining autonomy and local decision making. We support Canadian businesses in taking smart risks by delivering practical insurance solutions and exceptional service through trusted broker partnerships. We are seeking a technically savvy Data Engineer to join our fast-growing analytics team. You will design, build, and maintain robust data pipelines that power business insights across underwriting, claims, and policy administration. The role is hands on with Snowflake (including Openflow & Snowpipe), Microsoft SQL Server, PostgreSQL, Python, and Alteryx, and you’ll be instrumental in implementing a modern medallion architecture to ensure clean, trusted data for downstream analytics and reporting. If you enjoy turning messy source files, Excel spreadsheets, JSON payloads, or legacy system extracts into reliable, query ready datasets while automating validation and reconciliation, this is the perfect opportunity. Insurance domain knowledge is a plus but not required; we value strong data engineering fundamentals and a passion for continuous improvement.

Requirements

• You are a hands-on Data Engineer with strong experience in SQL, Python, and Snowflake, and a passion for building efficient, reliable data pipelines.
• You take ownership of data quality and performance, and enjoy turning complex data into clean, usable insights.
• Adaptable and collaborative, you work well across teams and continuously look for ways to improve processes and technology.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field (or equivalent practical experience).
• 3–5+ years of professional data engineering experience building production grade pipelines on cloud data warehouses (Snowflake preferred).
• Snowflake (core platform, Snowpipe, Openflow)
• Microsoft SQL Server
• PostgreSQL
• Python (pandas, sqlalchemy, pyarrow, etc.)
• Alteryx Designer & Server
• Data Extraction / Loading / Transformation (ELT)
• Medallion Architecture (Bronze/Silver/Gold)
• Data Reconciliation & Validation techniques
• Automation of Excel & JSON ingestion to RDBMS
• Git version control, CI/CD concepts

Nice To Haves

• Prior work in the insurance industry (underwriting, policy administration, claims)
• Exposure to a binder management system, such as VIPR or similar platforms
• Knowledge of data governance tools (e.g., Collibra, Alation)
• Experience with cloud orchestration / workflow tools (Azure Data Factory, Apache Airflow, Prefect)

Responsibilities

• Design & Develop Pipelines – Build scalable ELT pipelines using Snowpipe, Snowflake Openflow, Python scripts, and Alteryx workflows to ingest data from on premise SQL Server, PostgreSQL, Excel, JSON, and third party APIs.
• Implement Medallion Architecture – Create Bronze (raw), Silver (cleaned/standardized), and Gold (business ready) layers in Snowflake; enforce schema evolution, partitioning, clustering, and data retention policies.
• Data Quality & Reconciliation – Develop automated validation rules, record level reconciliation, and anomaly detection to guarantee data integrity across source systems and the data lake/warehouse.
• Automation & Orchestration – Use Snowflake Tasks, Streams, and external orchestration tools (e.g., Airflow, Azure Data Factory) to schedule, monitor, and recover pipelines without manual intervention.
• SQL Development & Optimization – Write performant T SQL, PostgreSQL/Redshift SQL, and Python based transformations; tune queries for large scale workloads.
• Collaboration & Documentation – Partner with data analysts, data scientists, product owners, and IT to gather requirements, document data lineage, and produce technical specifications.
• Continuous Improvement – Evaluate emerging tools (e.g., dbt, Fivetran), propose enhancements, and champion best practices for CI/CD, testing, and version control of data assets.
• Support & Incident Management – Provide tier 2 support for production issues, perform root cause analysis, and implement preventive fixes.

Benefits

• We believe in flexibility, authenticity, and growth: because when our people thrive, so does our business.
• TMCan offers the unique opportunity to work side by side with senior leaders, gaining direct exposure to strategic decision-making and business planning.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level