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.
LP
Senior Data Engineer
Posted via LinkedIn Recruiter (not a company profile)
Posted 1 hour ago
About the role
- Senior Data Engineer contract role: design/build ETL/ELT pipelines using Azure stack, primarily remote in Canada, occasional onsite in Edmonton.
Responsibilities
- Design, build, and maintain scalable, secure ETL/ELT data pipelines. Develop solutions using Python, PySpark, SQL, Azure Databricks, Azure Data Factory, Azure Synapse Analytics, Delta Lake, and Azure Data Lake Storage. Build analytics-ready datasets, lakehouse/warehouse models, semantic layers, data marts, fact tables, and dimensions. Integrate relational databases, APIs, files, cloud services, and other enterprise sources. Implement data quality, governance, metadata, lineage, security, monitoring, and troubleshooting practices. Support cloud modernization, data migrations, CI/CD, automation, and production operations. Collaborate with architects, product owners, business stakeholders, analysts, and Agile delivery teams. Use AI-assisted development tools to improve engineering, testing, documentation, and productivity.
Requirements
- Post-secondary education in Computer Science, Information Technology, Engineering, Mathematics, Statistics, Data Science, or related discipline. 10+ years of data engineering experience. 5+ years of hands-on Python/PySpark and SQL experience with enterprise ETL/ELT workflows. Strong experience building production data pipelines and integrating multiple data sources. Experience with enterprise cloud, lakehouse, or data warehouse platforms. Strong Git-based development and collaborative delivery experience. Ability to work remotely from within Canada and attend occasional meetings in Edmonton. Preferred: Production experience with Azure Databricks, Delta Lake, Microsoft Fabric, ADF, Synapse, Power BI, or comparable technologies. Dimensional modelling, semantic models, data migration, DevOps/CI/CD, infrastructure-as-code, REST APIs, and message queues. Experience with data governance, Microsoft SQL Server, public-sector delivery, or Government of Alberta environments. Experience applying AI tools in data engineering workflows.
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