Data Engineer - (Hybrid)

S

Shuvel Digital

Data Engineer - (Hybrid)

National
Part Time
Paid
  • Responsibilities

    Data Engineer
    Hybrid
    Vienna, VA, Winchester, VA and Pensacola, FL    .

    Job Description

    Design, develop, and optimize data pipelines and systems for the collection, connection, and storage of data. Manage, interpret, and derive insights from data. Implement data processing tasks, ensuring data quality and system reliability. Growing an understanding of business needs and objectives. Solve a range of mostly straightforward problems with some increased scope and complexity. Developing professional with basic skill set and proficiency with procedures and techniques.

    Responsibilities

    • Develop and maintain data pipelines and workflows.
    • Develop using SQL Server Integration Services.
    • Format data from APIs into SQL servers.
    • Collaborate with stakeholders to gather data requirements and ensure alignment with business needs and objectives.
    • Design and build data pipelines for data collection, connection, and storage.
    • Develop and enforce data engineering policies and best practices to ensure data integrity.
    • Ensure data quality and performance at scale.
    • Ensure high performance and scalability of data systems and processes.
    • Help with the collection, connection, and storage of data.
    • Optimize existing data workflows and ensure system reliability.
    • Collaborate with team members and participate in team projects and initiatives

    **
    Qualifications**

    • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
    • 3-5 years of experience in data engineering
    • Advanced knowledge of SQL language
    • Advanced understanding of API frameworks and JSON transformations
    • Basic understanding of business and operating environment
    • Basic knowledge of programming languages (Python, R, SQL, ).
    • Experience with data management, processing and analytic tools (Databricks).
    • Experience with data integration and processing tools.
    • Basic problem-solving skills.
    • Basic communication and collaboration skills.
    • Working experience with data warehousing solutions, ETL tools, and data system design.
    • Basic knowledge of data engineering principles, technologies, and architecture.