Data Engineer - Iowa

This position works on-site at downtown Des Moines, IA campus.

This position is responsible for ingesting, processing, transforming, and modeling data to ensure it is ready for consumption. This role involves working with complex data pipelines, designing efficient data architectures, and developing automated systems to guarantee the availability of clean, accurate, and structured data. The Data Engineer collaborates closely with cross-functional teams, including data scientists and data analysts, to improve operational efficiency by enhancing data flow, integration, and accessibility to support real-time decision-making, business intelligence, and analytical initiatives. Additionally, the Data Engineer plays a key role in identifying and addressing data quality issues, and implementing best practices for data governance and security.

Responsibilities:

Carrying out the Company's organizational values and operating in accordance with applicable laws, regulations, and Company policies are rquired functions. Essential and other important responsibilities and duties may include, but are not limited to, the following:

• Data Modeling: Develop and implement data models and schemas to support data integration, storage, and analytics, ensuring data is structured optimally for both transactional and analytical use cases. Develop and maintain data models that align with business requirements and optimize data storage. Merge data from diverse sources to create a unified view.
• Pipeline Development: Collaborate with data teams to understand data needs and design reusable, configurable data pipelines for efficient data ingestion. Build scalable pipelines for seamless ETL (Extract, Transform, Load) processes, integrating data from any source. Ensure timely, accurate data integration and transformation.
• Monitoring and Maintenance: Regularly monitor the health of data systems and pipelines, performing regular maintenance, and troubleshooting issues that arise. Identify poor performing processes to add efficiencies and lower overall costs. Ensure that processes alert when something does not work as expected so the team can respond accordingly.
• Data Quality & Consistency: Ensure data is accurate, consistent, and reliable. This involves identifying and fixing data issues, performing data validation, and ensuring data quality controls are in place.
• Performance Optimization: Optimize the performance of data systems to ensure they can handle large volumes of data efficiently and cost effectively. This might involve query optimization, partitioning strategies, or code efficiency enhancements.
• Documentation: Create and maintain clear documentation of data processes, architectures, and workflows for knowledge sharing.
• Security & Compliance: Ensure data is handled securely and in compliance with company policy and relevant regulations. This might include encryption, access controls, and auditing.
• Continuous Learning and Skill Development: Stay updated on the latest trends, tools, and best practices in data engineering and related fields. Encourage a culture of continuous improvement and innovation within the team.
• Perform other job-related duties and special projects as required.