Senior Azure Data Engineer to design/develop data pipelines, integrate data from various sources and ensure governance/quality for our enterprise utility c

Our client is looking for a Senior Azure Data Engineer to design/develop data pipelines, integrate data from various sources and ensure governance/quality for our enterprise utility client

**This is a hybrid role 3 days/week onsite in Edmonton or Calgary**

Must haves:

• 7+ years' experience as a Data Engineer or working in a similar role
• Design and build robust, scalable data pipelines using Databricks and Azure Data Services.
• Experience with Data Modeling and Database Design, Data Storage and Data Analytics
• Implementing data lakehouse architectures and optimizing ETL workflows for performance and cost efficiency.
• Experience with programming languages such as Python, Java, or Scala.
• Experience with data processing frameworks like Apache Spark, Hadoop, or similar.
• Experience in database and Extract-Transform-Load (ETL) architecture with Oracle, SQL Server and MySQL databases on multiple operating systems.

Nice to haves:

• Certifications: Relevant certifications in data engineering or cloud platforms.
• Machine learning: Knowledge of machine learning techniques and tools.

Responsibilities:

• Design and develop data pipelines: Create robust, scalable, and efficient data pipelines to process and manage large datasets.
• Data integration: Integrate data from various sources, including databases, APIs, and third-party systems, ensuring data consistency and quality.
• Data warehousing: Design and implement data warehousing solutions to support analytics and reporting.
• Performance optimization: Optimize and tune data processing systems for performance and cost efficiency.
• Data quality and governance: Implement data quality checks and governance practices to ensure data accuracy and compliance.
• Identify opportunities to enhance data quality, optimize data pipelines, and improve overall data infrastructure efficiency.
• Collaboration: Work closely with data architects, data scientists, analysts, and other stakeholders to understand their data needs and provide appropriate solutions.
• Documentation: Maintain clear and comprehensive documentation of data infrastructure, processes, and systems.
• Work with application, security, infrastructure, and other operational support teams, as well as project teams to resolve technical design, implementation, or operational technology issues
• Integrating data from multiple sources (databases, APIs, third-party systems) with strong quality and consistency controls.
• ITIL service delivery framework, including ITIL processes and best practices (including change management processes)
• Applying data governance and quality checks to ensure accuracy and compliance.
• Collaborating with Data Architects, Data Scientists, and Analysts to deliver secure, reliable, and accessible data for analytical products.
• Documenting infrastructure, processes, and systems for transparency and maintainability.