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
- Senior Data Engineer modernizing Alberta environmental regulatory data on Microsoft Azure. Building governed pipelines, APIs, and analytics-ready datasets for the DRAS platform.
Responsibilities
- Collaborate with business stakeholders and product owners to understand data product objectives, requirements, and success criteria
- Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure in cloud-native and hybrid environments
- Lead development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics
- Manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2 with the Data Architect
- Integrate diverse source systems, including ServiceNow and geospatial systems, using APIs, connectors, and custom scripts
- Develop and maintain data models and semantic layers for operational reporting, analytics, machine learning, and downstream consumption
- Build and optimize Python and SQL workflows for data cleansing, enrichment, and advanced analytics in Azure Databricks
- Design and expose secure data services and APIs using Azure API Management
- Implement metadata management, data classification, and lineage tracking
- Ensure privacy and regulatory compliance through role-based access controls, encryption, and data masking
- Monitor and troubleshoot data pipelines and integrations for reliability, scalability, and performance
- Use AI and automation tools for pipeline development, testing, monitoring, and documentation
- Leverage AI-assisted tools for code generation, optimization, and review
- Design and curate standardized, high-quality datasets for advanced analytics and future AI use cases
- Perform other duties as needed
Requirements
- Experience designing scalable, secure, and high-performance data architecture on Microsoft Azure
- Experience with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics
- Experience managing Azure Data Lake Storage Gen2
- Experience integrating ServiceNow and geospatial systems using APIs, connectors, and custom scripts
- Proficiency in Python and SQL
- Knowledge of data modeling and semantic layers
- Knowledge of Azure API Management
- Knowledge of metadata management, data classification, and data lineage
- Knowledge of role-based access controls, encryption, and data masking
- Knowledge of FOIP and GDPR compliance
- Ability to use AI and automation tools for data engineering workflows
- Ability to use AI-assisted tools for code generation, optimization, and code review
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Degree requirement
No Education Requirement
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