Description

Job Description

Key Responsibilities:

  • Design, build, and maintain scalable data pipelines and ETL workflows to support the enterprise lake house platform.
  • Work closely with data scientists, analysts, and business teams to gather data requirements and deliver robust data solutions.
  • Develop and implement data ingestion, transformation, and integration using big data technologies such as Hadoop, Spark, and Kafka.
  • Manage and optimize data storage systems, including data lakes and warehouses, hosted on cloud platforms like AWS, Azure, or Google Cloud.
  • Ensure high data quality, consistency, and dependability through comprehensive data validation and monitoring practices.
  • Create and maintain clear documentation for data workflows, system architecture, and related processes.
  • Diagnose and address data issues and performance inefficiencies.
  • Keep up with emerging trends and advancements in big data and data engineering technologies.

Requirements:

  • Bachelor’s degree in computer science, Information Technology, or a related field.
  • Proven experience as a Data Engineer, preferably in big data or cloud-based projects.
  • Strong understanding of data lake and data warehouse concepts, architectures, and technologies.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, Google Cloud). 
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Familiarity with data governance and security best practices.

Education

Bachelor’s degree in computer science, Information Technology