Data Engineering Leader

2 months ago

Vancouver, British Columbia, Canada Amazon Data Services Canada, Inc. Full time

About Amazon Data Services Canada, Inc.

At Amazon Data Services Canada, Inc., we are dedicated to building innovative data solutions that power our global operations and drive customer success. Our team is passionate about leveraging the latest technologies to create impactful and scalable systems.

About the Role:

We are seeking a talented and experienced Data Engineering Leader to join our growing team. In this role, you will play a pivotal part in developing and maintaining data infrastructure that supports our sustainability initiatives. You will lead a team of engineers, guiding them towards best practices and fostering a culture of innovation.

Key Responsibilities:

  • Lead and mentor a team of data engineers, providing technical guidance and support.
  • Define the vision and priorities for the team, ensuring alignment with overall business objectives.
  • Design, develop, and maintain robust data pipelines and systems that process large volumes of sustainability-related data.
  • Collaborate closely with product managers, software developers, and other stakeholders to ensure seamless integration of data solutions.
  • Promote a culture of continuous improvement by identifying opportunities for optimization and automation.

Qualifications:

  • 6+ years of experience in data engineering, database engineering, business intelligence, or business analytics.
  • Strong understanding of software development best practices and the full software development lifecycle.
  • Proficiency in at least one modern scripting or programming language (e.g., Python, Java, Scala).
  • Experience building data products incrementally and integrating data sets from diverse sources.
  • Proven ability to provide technical leadership and mentor other engineers.
  • Familiarity with cloud computing platforms, particularly AWS services such as Redshift, Glue, S3, and Step Functions.

Preferred Qualifications:

  • Experience with big data technologies (e.g., Hadoop, Hive, Spark, EMR).
  • Knowledge of carbon accounting protocols (e.g., GHG Protocol).

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