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Senior Azure Data Engineer to design/develop data pipelines, integrate data from various sources and ensure governance/quality for our enterprise utility client
Senior Azure Data Engineer to design/develop data pipelines, integrate data from various sources and ensure governance/quality for our enterprise utility clientS.i. Systems • Edmonton
Senior Azure Data Engineer to design / develop data pipelines, integrate data from various sources and ensure governance / quality for our enterprise utility client

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

S.i. Systems • Edmonton
Il y a 3 jours
Type de contrat
  • Temps plein
Description de poste

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 checksto 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.
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