About the role

  • Senior Cloud Data Engineer responsible for operating and optimizing cloud-based data environments. Collaborating with analytics teams and specializing in AWS, Databricks, and Spark technologies.

Responsibilities

  • Responsible for operating and optimizing our cloud-based data processing environment.
  • Work with Databricks, AWS services, Spark, Unity Catalog, and Delta Lake to ensure efficient, secure, and reliable data pipelines and analytics workloads.
  • Refines data transformations using PySpark and Spark SQL within notebooks.
  • Leverages orchestration tools like Apache Airflow to automate data workflows.
  • Participates in code reviews, testing, and documentation.
  • Supports and troubleshoots Databricks jobs, Spark workloads, and AWS-based data processes
  • Optimizes Databricks clusters and jobs for performance and cost.
  • Works closely with data engineering and analytics teams to improve data quality.

Requirements

  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or similar
  • Master’s Degree will be considered as an asset
  • 5+ years of experience in big data operations or cloud-based data engineering.
  • Strong hands-on experience with AWS, Databricks, Delta Lake, and Apache Spark
  • Proficient in Python, SQL, and PySpark
  • Experience with CI/CD, version control, and release processes (AWS CodePipeline, Git)
  • Experience with monitoring, debugging, and optimizing ETL/ELT and Spark workloads
  • Knowledge of data governance frameworks and exposure to enterprise security or regulated environments will be considered as an asset
  • **Competencies**
  • Excellent problem-solving skills and attention to detail
  • Strong communication skills and the ability to work collaboratively in a team environment
  • Effective time management with ability to multi-task and prioritize work

Job title

Senior Cloud Data Engineer

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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