The Data Engineer at Workiva will be an instrumental part of data workflows throughout the organization. You will build distributed services to support multiple data analytics teams and business intelligence engineers reliably and at scale using AWS cloud environments. Provide cutting edge, reliable, and easy to use systems for ingesting and processing data and help the teams that build data intensive applications be successful. This role will collaborate with many cross functional teams on the planning, execution, and successful completion of technical projects with the ultimate purpose of improving customer experience. The role will build and maintain batch and real-time data flows used for business intelligence, analytics, and machine learning within all organizations across Workiva. This also involves storing and exposing data via a Database, Data Lake, and other APIs. This role will work primarily with other Data Engineers, but also Data Scientists, ML Engineers, and business partners to ensure quality, reliability and performance at the highest level.
What You’ll Do
- Develop data extraction and integration code modules for batch and incremental data flow from various data sources using new and existing patterns.
- Use existing tools and processes to deploy to integration and production environments. Assist in maintaining the deploy processes.
- Maintain the health of the data ecosystem by configuring monitors, defining alerts on common failure points and giving feedback on data quality to data owners and business partners.
- Test software, validate data and write automated tests (unit, integration, functional, etc.).
- Review peer code and submit thorough and actionable feedback based on team standards and industry best practices.
- Triage and resolve production issues. Communicate with individual business partners on status. Escalate as needed.
- Design data lake storage and access patterns to match customer requirements and conform to naming standards.
- Understand the data at a deep level and apply security appropriately, escalate as needed.
- Tune processes and SQL to reduce cost and wait time. Implement systems to balance data volume, latency and customer requirements.
- Work with business partners to write requirements and test deployed code.
- Join rotation to support production workflows during off hours.
What You’ll Need
- Undergraduate Degree or equivalent combination of education and experience in a related field.
- Bachelor’s degree in Computer Science, Engineering, Math, Finance, Statistics or related discipline
- Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams
- Strong planning and organizing skills to prioritize numerous projects and ensure data is delivered in an accurate and understandable manner to the end user
- 2+ years of relevant experience in the data engineering role, including data warehousing and business intelligence tools, techniques and technology, or experience in analytics, business analysis or comparable consumer analytics solutions
- Statistics experience preferred
- Experience in big data processing and using databases in a business environment with large-scale, complex datasets. (SQL, Hadoop, Spark, Flink, Beam etc)
- Knowledge and direct experience using business intelligence reporting tools. (Quicksight, Tableau, Splunk etc.)
- Extensive knowledge of SQL query design and tuning for performance and accuracy
- Experience with Python, R, or other data relevant scripting languages preferred
- Experience with Data Lake design and philosophy
- Experience in an Agile/Sprint working environment preferred
- Proficient research skills to locate market information using numerous internal and external sources of data