Data Engineer - On-Site [see locations]

Regions Bank•Atlanta, GA

9h•Onsite

About The Position

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.

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
Strong experience with SQL databases, including development and support of SSIS/SSRS packages
Hands-on experience with PostgreSQL in a production environment
Proven ability to develop, manage, and maintain ETL pipelines
Working experience in AWS cloud environments
Experience using Python for data processing and automation
Required experience with Apache Kafka for data streaming
Required experience with Snowflake for cloud data warehousing

Nice To Haves

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
Experience building data solutions at scale
Experience designing and building relational data structures in multiple environments
Experience with DevOps principals, CI/CD, and Software Development Lifecycle
Experience with No-SQL databases
Experience with large-scale data Lakehouses at Enterprise scale
Proven record of accomplishment of delivering operational Data solutions including Report and Model Ready Data Assets
Significant experience working with senior executives in the use of data, reporting and visualizations to support strategic and operational decision making
Strong ability to transform and integrate complex data from multiple sources into accessible, understandable, and usable data assets and frameworks
Strong background in synthesizing data and analytics in a large (Fortune 500), complex, and highly regulated environment
Strong technical background including database and business intelligence skills
Strong communication skills through written and oral presentations

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