The DataOps engineer maintain and prepare data processing infrastructure to support large and complex use cases throughout the enterprise. The person in this role, creates scalable and reusable solutions for gathering, collecting, storing, processing, and serving data on both large and very large (i.e. Big Data) scales. These solutions can include solutions in any of the following domains: ETL, business intelligence, analytics, persistence (relational, NoSQL, data lakes), search, data warehousing, stream processing, and machine learning.
- Assists in the development of large-scale data structures and pipelines to organize, collect and standardize data that helps generate insights and addresses reporting needs.
- Applies understanding of key business drivers to accomplish own work.
- Writes ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing.
- Integrates data from a variety of sources, assuring that they adhere to data quality and accessibility standards.
- Plan and work on internal projects as needed, including legacy system replacement, monitoring and analytics improvements, tool development, and technical documentation.