Data Engineering Principal

3 days ago

London, Greater London, United Kingdom Metyis Full time

About the Role

Metyis is seeking a highly skilled Data Engineering Principal to join our team. As a key member of our organization, you will be responsible for leading the design and execution of data engineering projects, collaborating with clients to execute their data strategies, and engineering complete technical solutions to solve business challenges.

Key Responsibilities

  • Lead and manage the design and execution of data engineering projects, including ETL pipelines, data anonymization pipelines, data lakes, and near real-time streaming data hubs.
  • Support clients in executing their data strategies by designing and building operational data platforms, including web services, training and scoring machine learning model operationalization.
  • Engineer complete technical solutions to solve concrete business challenges in areas such as digital marketing, eCommerce, Business Intelligence, and self-service analytics.
  • Troubleshoot and QA work done by team members, ensuring data engineering best practices.
  • Collaborate closely with partners, strategy consultants, and data scientists in a flat and agile organization where personal initiative is highly valued.
  • Advise clients on the implementation of effective data governance processes.
  • Lead knowledge sharing sessions with peers, client prospects, and clients.
  • Communicate and interact with clients at the executive level.
  • Guide and mentor team members.

Requirements

  • BSc or MSc in Computer Science, IT, or relevant fields desirable.
  • 8+ years of professional experience in the Data Engineering domain.
  • Excellent command of both verbal and written English.
  • The ability to draw inferences from complex and diverse data.
  • Experience designing and setting up modern data lake architectures.
  • Proven experience in SQL.
  • Experience using Version Control (e.g. Git), Testing, and CI/CD.
  • Experience in the automation of data quality monitoring.
  • Experience of creating data workflows on one of the leading cloud platforms – Azure, AWS, or GCP.
  • Knowledge of good data governance practices across the data lifecycle.

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