Data Engineer

Everest TechnologiesColumbus, OH
2dRemote

About The Position

We are seeking a highly skilled and motivated Data Engineer to join our team in a critical, urgent role. This position is key to building and maintaining robust data solutions. The ideal candidate will possess a strong foundation in data warehousing principles and a keen design mindset to handle complex data challenges.

Requirements

  • ETL/ELT Development: Strong experience in designing and building data pipelines using ETL/ELT tools and frameworks.
  • SQL: Advanced proficiency in SQL for data manipulation, transformation, and optimization.
  • Experience with EPIC EMR and Informatica is required.
  • Programming: Strong programming skills in Python (or a similar language) for scripting, automation, and data processing.
  • Data Warehousing: Experience with data warehousing concepts and technologies.
  • Cloud Computing: Hands-on experience with at least one major cloud platform's data services (e.g., Microsoft Azure Data Factory, Azure Fabric, IICS).
  • Version Control: Proficiency with Git for code management and collaboration.
  • Problem-Solving: Proven ability to troubleshoot and resolve data pipeline issues.
  • Data Modeling: Experience with various data modeling techniques (e.g., dimensional modeling).
  • Real-time Processing: Familiarity with real-time data streaming technologies (e.g., Kafka, Azure Event Hubs).
  • Education: Bachelor's degree in Computer Science, Engineering, or related field.

Nice To Haves

  • Epic Experience: Highly preferred, but not a mandatory requirement.

Responsibilities

  • Design, build, and maintain scalable and efficient ETL/ELT data pipelines to ingest data from internal and external sources (e.g., APIs from EPIC, Workday, relational databases, flat files). and data warehouse to ensure data is clean, accessible, and ready for analysis and model training.
  • Collaborate with the Data Analyst and other stakeholders to understand their data requirements and provide them with clean, well-structured datasets.
  • Implement data governance, security, and quality controls to ensure data integrity and compliance.
  • Automate data ingestion, transformation, and validation processes.
  • Work with our broader IT team to ensure seamless integration of data infrastructure with existing systems.
  • Contribute to the evaluation and implementation of new data technologies and tools.
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