( 1 or 2 days onsite per week in Downtown Toronto) . We are seeking a skilled Python Developer with strong experience in data engineering, data processing, and analytics within the insurance domain. The successful candidate will work closely with business stakeholders, data engineers, analysts, and other data team members to design, develop, and maintain scalable data solutions that support policy, claims, underwriting, finance, and operational reporting initiatives.
The ideal candidate will possess strong Python development skills, hands-on experience working with large datasets, and a solid understanding of insurance data structures and business processes. Experience with Databricks, Apache Spark, and modern cloud-based data platforms is considered a strong asset.
Key Responsibilities
- Design, develop, and maintain scalable data processing pipelines using Python.
- Build and optimize data ingestion, transformation, validation, and enrichment processes.
- Analyze and process structured and semi-structured datasets including policy, claims, underwriting, billing, and financial data.
- Collaborate closely with data engineers, data analysts, architects, and business stakeholders to deliver data solutions aligned with business requirements.
- Develop reusable frameworks and utilities for data quality, reconciliation, and monitoring.
- Support data integration efforts across internal systems and third-party insurance platforms.
- Troubleshoot data issues, perform root cause analysis, and implement corrective actions.
- Participate in Agile ceremonies, sprint planning, and peer code reviews.
- Contribute to technical documentation, data lineage, and data governance initiatives.
- Work collaboratively with cross-functional data teams to support enterprise reporting, analytics, and modernization initiatives.
Required Qualifications
- 5+ years of experience developing data solutions using Python.
- Strong experience with:
- Python
- Pandas
- NumPy
- SQL
- REST APIs
- Experience building ETL/ELT pipelines and large-scale data processing solutions.
- Hands-on experience working with relational and cloud-based data platforms.
- Strong understanding of data modeling, data quality, and data validation practices.
- Experience processing large datasets in enterprise environments.
- Familiarity with Git, CI/CD, and Agile delivery methodologies.
- Excellent communication and collaboration skills.
Insurance Domain Experience
Candidates should have experience working with one or more of the following insurance data domains:
- Policy Administration
- Claims Processing
- Underwriting
- Billing & Payments
- Premium Reporting
- Reinsurance
- Actuarial Data
- Regulatory & Compliance Reporting
Preferred Qualifications
- Experience with Databricks and Apache Spark.
- Experience with Azure Data Platform services (Azure Data Factory, Azure Data Lake, Synapse, Fabric) or AWS data services.
- Experience working with Delta Lake and Lakehouse architectures.
- Exposure to machine learning, predictive analytics, or AI-enabled data solutions.
- Experience integrating data from Guidewire, Duck Creek, Insurity, or other insurance platforms.
- Knowledge of insurance reporting and analytics frameworks.
Technical Environment
- Python
- SQL
- Databricks (Preferred)
- Apache Spark (Preferred)
- Azure / AWS Cloud Services
- Git
- CI/CD Pipelines
- REST APIs
- Data Warehousing & Analytics Platforms
Soft Skills
- Strong analytical and problem-solving abilities.
- Ability to work effectively in a collaborative team environment.
- Excellent stakeholder communication and requirement-gathering skills.
- Self-motivated with strong attention to detail.
- Comfortable working in a hybrid environment with regular onsite collaboration.
This role offers an opportunity to contribute to large-scale insurance data modernization initiatives while working alongside experienced data professionals in a collaborative and highly technical environment.
Experience:
- Data Bricks: 2 years (required)
Work Location: Hybrid remote in Toronto, ON (Toronto District)
