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 government regulatory data platforms. Building governed Azure pipelines, models, APIs, and analytics-ready datasets for DRAS.
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 efficient access and governance
- Integrate data from diverse source systems, including ServiceNow and geospatial systems, using APIs, connectors, and custom scripts
- Develop and maintain data models and semantic layers for reporting, analytics, machine learning, and downstream consumption
- Build and optimize Python and SQL data workflows for 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
- Use 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 cloud-native and hybrid environments
- Experience developing data ingestion, transformation, and integration pipelines
- Proficiency with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics
- Experience managing Azure Data Lake Storage Gen2 and structured storage solutions
- Experience integrating ServiceNow and geospatial systems using APIs, connectors, and custom scripts
- Experience developing data models and semantic layers for reporting, analytics, and machine learning
- Proficiency in Python and SQL
- Experience with Azure API Management and secure data services/APIs
- Knowledge of metadata management, data classification, and lineage tracking
- Knowledge of privacy and regulatory standards including FOIP and GDPR
- Knowledge of role-based access controls, encryption, and data masking
- Experience monitoring and troubleshooting data pipelines and integrations
- Experience using AI and automation tools for data engineering workflows
- Experience with AI-assisted code generation, optimization, and review
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
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