Senior Data Engineer
Senior Data Engineer builds and maintains scalable data pipelines using Azure, Databricks, and Power BI to support government digital transformation and analytics.
- Compensation
- CA$90–CA$115 / hr
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Senior-level experience in Data Engineering.
- Strong experience with data pipelines and ETL/ELT.
- Experience with Azure, Databricks, Microsoft Fabric, or similar cloud platforms.
- Strong SQL and data modeling skills.
- Experience with Azure Data Factory/Fabric Data Factory, SSIS, Dataflows, or Notebooks.
- Strong understanding of data warehouses, data lakes, star/snowflake schemas, fact and dimension tables.
- Strong Power BI and DAX experience.
- Experience with Python and/or R.
- Experience with CI/CD and automated deployment.
- Experience integrating APIs, databases, NoSQL platforms, and files.
- Knowledge of data quality, governance, security, and access management.
- Strong communication and stakeholder-management skills.
- Experience working in Agile/multidisciplinary environments.
Full description
Senior Data Engineer
emergiTEL is hiring a Senior Data Engineer for our client in the public sector / government services industry. This is a 12-month contract role.Duration: 12 months
Pay: $90/hr - $115/hr INC
Location: Edmonton, Alberta — Remote
Work Arrangement: Remote within Canada, with occasional meetings/work sessions in Edmonton
Industry: Public Sector / Government Digital Services
Role Overview
Our client is seeking a Senior Data Engineer to support modern digital transformation initiatives. The successful candidate will work within multidisciplinary Agile teams to design, develop, and maintain modern data solutions that improve data quality, accessibility, analytics, and decision-making.
The role combines data engineering, cloud platforms, data integration, analytics, reporting, and data governance.
Key Responsibilities
- Design, build, and maintain scalable data pipelines across on-premises and cloud environments.
- Develop data solutions using Azure, Databricks, Microsoft Fabric, GCP, and AWS.
- Develop and optimize ETL/ELT processes using SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks.
- Build and maintain dimensional data models, including star and snowflake schemas.
- Integrate data from relational databases, NoSQL platforms, APIs, and files.
- Implement data validation, error handling, logging, monitoring, and scheduling.
- Optimize high-volume data processing and improve pipeline performance.
- Implement CI/CD practices for automated data pipeline deployment and operations.
- Support data lakes, data warehouses, security controls, access management, and data governance.
- Develop Power BI dashboards and reports using DAX.
- Analyze datasets to identify trends, patterns, and anomalies.
- Use Python and/or R for statistical analysis and predictive/descriptive modeling.
- Prepare curated data marts, fact tables, and dimension tables for analytics.
- Collaborate with architects, developers, business stakeholders, and product teams.
- Present complex data findings in a clear and actionable manner.
- Support Agile delivery and mentor teams on analytics and data practices.