Job description

Job Description

Job Description

Key Responsibilities
  • Develop, Maintain, support, and enhance the business intelligence data backend, including data warehouses and data lakes.
    • Performs needed assessments
    • Implement data transformations and data structures for data warehouse and lake/repository.
    • Process data using spark (PySpark)
    • Manage cloud and/or on-premises solutions for data transfer and storage.
    • Establish data structures for all enterprise data stored in business intelligence systems.
  • Collaborate and work with data analysts in various functions to ensure that data meets their reporting and analysis needs.
    • Establish interfaces between the data warehouse and reporting tools, such as PowerBI.
    • Assist data analysts with connecting reporting and analytics software to data warehouses, lakes, and other data sources.
    • Develop, create, maintain, and enhance the data pipelines using kafka over a variety of systems.
    • Manage access and permissions to data.
Required Skills
  • Bachelor’s Degree plus at least 5-7 years of experience with minimum 3+years in Data lakes and processing data using Spark. AWS S3 and PySpark preferred
  • Experience with working on any ETL tool, managing data warehouse and/or business intelligence systems. An advanced degree or certifications in a related field is a plus.
Knowledge, Skills & Abilities
  • Demonstrated experience with setting up data structures (tables and views) for use with modern analytics software.
  • Expertise with Amazon Web Services, kafka, Spark programming, SQL-based database systems, and/or other enterprise data warehouse solutions.
  • Experience working with programming languages used in ETL and/or ELT environments, such as SQL and Python.
  • Experience working with DevOPS tools like Jenkins, Ansible, Terraform, GitHUB.
  • Eperience / exposure to Java is a plus.
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