Data Engineer On-Site

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Job Description:

At Regions, the Data Engineer focuses on the evaluation, design, and execution of data structures, processes, and logic to deliver business value through operational and analytical data assets. The Data Engineer uses advanced data design and technical skills to work with business subject matter experts to create enterprise data assets utilizing state of the art data techniques and tools.

Primary Responsibilities

• Partners with Regions Technology partners to Design, Build, and Maintain the data-based structures and systems in support of Data and Analytics and Data Product use cases

• Builds data pipelines to collect and arrange data and manage data storage in Regions’ big data environment

• Builds robust, testable programs for moving, transforming, and loading data using big data tools such as Spark

• Coordinates design and development with Data Products Partners, Data Scientists, Data Management, Data Modelers, and other Technical partners to construct strategic and tactical data stores

• Ensures data is prepared, arranged and ready for each defined business use case

• Designs and deploys frameworks and micro services to serve data assets to data consumers

• Collaborates and aligns with technical and non-technical stakeholders to translate customer needs into Data Design requirements, and work to deliver world-class visualizations, data stories while ensuring data quality and integrity

• Provides consultation to all areas of the organization that plan to use data to make decisions

• Supports any team members in the development of such information delivery and aid in the automation of data products

• Acts as trusted adviser and partner to business leads- assisting in the identification of business needs & data opportunities, understanding key drivers of performance, interpreting business case data drivers, turning data into business value, and participating in the guidance of the overall data and analytics strategy

This position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay.

Requirements

• Bachelor’s degree and six (6) years of experience in a quantitative/analytical/STEM field or technical related field

• Or Master’s degree and four (4) years of experience in a quantitative/analytical/STEM field or technical related field

• Or Ph.D. and two (2) years of experience in a quantitative/analytical/STEM field

• Three (3) years of working programming experience in Python/PySpark, Scala, SQL

• Three (3) years of working experience in Big Data Technology in Hadoop, Hive, Impala, Spark, or Kafka

Preferences

• Background in Big Data Engineering and Advanced Data Analytics

• Experience developing solutions for the financial services industry

• Experience in Agile Software Development

• Experience or exposure to cloud technologies and migrations

• Prior banking or financial services experience

Skills and Competencies

• Experience building data solutions at scale

• Experience designing and building relational data structures in multiple environments

• Experience with Dev Ops principals, CI/CD, and Software Development Lifecycle

• Experi…