Data Engineer

Sterling Jewelers   •  

Akron, OH

Industry: Retail / Diversified


Less than 5 years

Posted 424 days ago

This job is no longer available.

Prepares and processes large data sets (structured and unstructured) through queries, scripts, and ETLs to facilitate accurate reporting and statistical analysis per the requirements of data scientists and analysts.

Design and develop big data solutions using industry standard technologies. Analyze business requirements and develop long-term data warehousing strategies leveraging state of the art big datatechnology. Work with internal and external customers to overcome technical obstacles, answering questions and proposing solutions pro-actively.

Utilizing big data tools, gather, collect and store data. Complete batch processing or real-time processing to provide in a ready-to-query and analyze format. Map and document data into a standardized set of facts and dimensions. Create aggregates for use in reporting and analytics.

Monitor the system, log and troubleshoot errors, build human-tolerant pipelines and address continuous integration. Perform data audits on client data sets to test domain and range values, patterns and build a plan for doing data quality assessments and clean up.

Follow best practices for testing, capacity planning, documentation, monitoring, alerting and incident response. Ensure compliance of acquisition, storage and analysis of data.

Collaborate with team to build and design core technologies. Demonstrate strong implementation aptitude to translate objectives into a scalable solution to meet the needs of the end customer while meeting deadlines.


  • Bachelor's degree in a Statistics, Mathematics, Economics, Computer Science or related
  • 3-5 years’ software engineeringexperience
  • Big Data and software engineeringexperiencerequired
  • Self-starter with the ability to adapt and learn quickly.
  • Have a passion for developing and deploying data models.
  • Experience with deployment of analytics software.
  • Demonstrated knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems and content delivery network.
  • Use of data blending software such as Alteryx and SAS.
  • Experience in enterprise data governance.