Data Engineer

Industry: Telecommunications
Remote
Company size: 251-10K
Full-time

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Job description

A well-established platform on a mission to become the best in the gaming industry is looking for a Data Engineer. The engineer will be in charge of bringing a rich blend of technical strength, engineering excellence, business acumen, and the ability to operate in a very fast-moving environment to deliver value quickly and in an agile fashion. The company strives to bring sports fans unrivaled digital sports and gaming entertainment experiences by leveraging the power of modern technology. This is an excellent opportunity for developers to join a hyper-growth startup that’s redefining its industry.

 

Job Responsibilities:

  • Design, build and manage robust and scalable Data Warehouse/ETL infrastructures and scalable data pipelines
  • Test build systems and processes using standard automated data quality monitoring approaches
  • Rapidly evolve the Data Platform to supply the increasingly data-led needs of the business
  • Modify and improve features and troubleshoot recurring problems to optimize for performance and scalability
  • Build products ensuring data privacy and security 
  • Build on the Azure SQL/Synapse-based cloud data warehouse, and embrace technologies like real-time processing and universal event logging
  • Constantly look for things to improve, fix recurring problems, deliver small but helpful features, and optimize for performance and scalability
  • Collaborate with both business stakeholders and product engineering teams

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5-7 years of relevant experience as a Data Engineer
  • 5+ years of working experience with T-SQL and MySQL
  • 2+ years of experience with Azure Data Lake
  • Demonstrable experience with Python and related technologies
  • Should be well-versed and possess proven experience in working with AWS, Google Cloud Platform, Spark, and Twitter API
  • Knowledge of developing data engineering trends and best practices
  • Ability to collaborate with multidisciplinary teams
  • Strong written and verbal communication skills with fluency in English

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