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Data Engineering Manager

THE ROLE

The Data Engineering Manager is responsible for leading a team of data engineers in designing, developing, and maintaining the organization’s data infrastructure. This role ensures the efficient and reliable processing of data, enabling data-driven decision-making across the organization. The Data Engineering Manager collaborates with cross-functional teams to implement best practices and innovative solutions in data management and analytics.

WHAT WILL YOU BE RESPONSIBLE FOR?

  • Leading, mentoring, and developing a team of data engineers.
  • Overseeing the design, implementation, and
    maintenance of scalable data pipelines.
  • Planning, prioritising, and managing multiple data engineering
    projects.
  • Working closely with Analytics, and other stakeholders to
    understand data needs and deliver solutions.
  • Staying updated with the latest trends and technologies
    in data engineering.
  • High-quality, scalable data pipelines and ETL
    processes.
  • Reliable and secure data storage solutions.
  • Comprehensive documentation of data engineering
    processes and systems.
  • Regular reports on data pipeline performance and
    data quality metrics.
  • Training and development plans for the data
    engineering team.

WHAT TYPE OF CANDIDATE ARE YOU?

  • Ability to inspire and lead a team, fostering a positive
    and productive work environment. (Managerial
    experience is required)
  • Extensive experience in leading the design and
    development of large-scale data processing
    applications and infrastructure.
  • Expert-level knowledge of the end-to-end data
    engineering process, demonstrating mastery in
    designing and implementing scalable solutions.
  • Exceptional analytical skills with a track record of
    providing strategic insights and proposing innovative
    solutions.
  • Proficiency in advanced data engineering tools,
    frameworks, and languages.

WHAT TECHNICAL SKILLS WILL YOU HAVE?

  • Must have: Python, SQL
  • Desired: AWS, Docker, Kafka, Airflow, Redshift, S3

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