Data Engineer

Description:

• Bachelors Degree in Computer Science, Software Engineering, Informatics, or Information Systems.
• A Degree from an accredited institution is essential to ensure foundational knowledge in programming, algorithms, and software design.
• Equivalent qualifications or certifications combined with significant industry experience may also be considered.
• Relevant certifications (e.g., Microsoft Certified: Azure Data Engineer Associate, Power BI Data Analyst, MCSA/MCSE SQL Server 2012/2014) are a plus.
  Required Minimum Work Experience:
  
  • 3-5 years of professional experience in a Data Engineer or related role.
    Technical Competencies
    
    • At least 3 years of experience working with Microsoft SQL Server, Sybase, or Postgres SQL.
    • Familiarity with NoSQL DB systems.
    • Strong T-SQL knowledge.
    • Intermediate Python development and familiarity with data-related libraries (Pandas, PySpark, NumPy, etc.).
    • Experience with ETL/ELT tools such as SSIS, Data Factory, Synapse, AirFlow, or similar tools for AWS (e.g., Glue, Fire Hose).
    • SQL Internals statistics, execution plans, wait types, isolation levels, DMVs, indexes.
    • Understanding of Hadoop, Spark, MapReduce, columnar databases, and Massive Parallel Processing systems.
    • Setting up data ingestion processes in Azure, AWS, or GCP.
    • Experience with visualization tools such as Power BI, SSRS, Tableau, or QlikView.
    • Knowledge of writing and optimizing complex queries with 3-5 years expertise.
    • Version Control and CI/CD:
      
    • Proficient in using Git and working with repositories like GitHub or Bitbucket.
  • Familiarity with CI/CD pipelines and deployment strategies.
  • Advantageous Skills:
  • Experience in C# or Java and its ecosystem.
• Understanding of microservices architecture and containerization (e.g., Docker, Kubernetes).
  Key Performance Areas:
  
• Maintain and Enhance Existing Systems:
• Identify and resolve issues in existing software systems.