Sr. Data Engineer - Analytics

ScoularOmaha, NE
3h

About The Position

The Senior Data Engineer will be a key contributor in designing, building, and optimizing data solutions that power our analytics ecosystem. This role focuses on hands-on development, ensuring data integrity, performance, and scalability across our platforms. The Senior Data Engineer will collaborate closely with leads, analysts, and business stakeholders to deliver high-quality data products and solutions.

Requirements

  • 5+ years of experience in data engineering and analytics, with strong expertise in ETL/ELT processes including using medallion framework.
  • Proficiency in PySpark and Azure Data Services (Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage Gen2, Azure SQL Databases).
  • Experience working with Parquet and Delta file formats.
  • Familiarity with architecture involving Warehouse, Lakehouse, and operational data stores.
  • Knowledge of CI/CD pipelines using Azure DevOps and Agile development methodologies.
  • Bachelor’s Degree in Computer Science, MIS, or related field (or equivalent experience).
  • Excellent problem-solving skills and ability to work independently or in a team environment.
  • Strong communication skills to collaborate effectively across technical and business teams.

Nice To Haves

  • Working knowledge of Microsoft Fabric and Power BI (development and optimization).
  • Experience with API connectivity
  • Exposure to Databricks, Snowflake, or similar platforms.
  • Understanding of data governance, lineage, and audit logging.

Responsibilities

  • Design, develop, and maintain scalable data pipelines and integration solutions by analyzing business requirements and system dependencies to deliver efficient, reliable, and secure data solutions.
  • Build and optimize ETL/ELT workflows using pipeline and PySpark frameworks, following medallion architecture principles.
  • Implement best practices for data modeling, performance tuning, and scalability across data platforms.
  • Work with modern file formats (e.g., Parquet, Delta) to ensure efficient storage and processing.
  • Ensure data quality, security, and compliance across all solutions.
  • Monitor and maintain data systems, proactively identifying and resolving performance issues.
  • Collaborate with cross-functional teams to deliver integrated solutions for complex business problems.
  • Stay current with emerging technologies and recommend improvements to enhance the data ecosystem.
  • Contribute to documentation and knowledge sharing within the team.
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