Populus Group - Troy, MI

posted about 2 months ago

Full-time
Troy, MI
Administrative and Support Services

About the position

As a Data Engineer at Populus Group LLC, you will be responsible for designing strategies and developing comprehensive database architectures that meet the needs of our organization. This role requires you to set standards for database operations, programming, query processes, and security protocols to ensure the integrity and efficiency of our data systems. You will monitor and support data pipelines, optimizing data workflows to enhance performance and reliability. Additionally, you will integrate new systems with our existing data warehouse structure, refining system performance and functionality to align with business objectives. Your work will primarily involve utilizing a variety of tools, with a strong emphasis on PySpark, Databricks, and Azure. You will ensure the reliability and performance of our cloud environment, which is critical for our data operations. This position is based in Troy, MI, but may require travel to various unanticipated locations throughout the United States, which could involve relocation. Your ability to adapt to different environments and work collaboratively with cross-functional teams will be essential for success in this role.

Responsibilities

  • Design and develop database architectures.
  • Set standards for database operations, programming, and security.
  • Monitor and support data pipelines and optimize workflows.
  • Integrate new systems with existing data warehouse structures.
  • Refine system performance and functionality.
  • Ensure reliability and performance of cloud environments.

Requirements

  • Master's Degree or above in a relevant field.
  • Experience with database architecture design.
  • Proficiency in PySpark, Databricks, and Azure.
  • Strong understanding of database operations and security standards.
  • Ability to monitor and optimize data workflows.

Nice-to-haves

  • Experience with cloud environments and data integration.
  • Familiarity with data warehousing concepts.
  • Knowledge of data pipeline monitoring tools.
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