Cloud Data Engineer - AI Platform

Regions Bank•Hoover, AL

23h•Onsite

About The Position

At Regions, the Cloud Data Engineer supports the Data and Analytics organization by assisting in the design, optimization, and development of data pipelines and machine learning models. The role works on cross-functional teams to develop reusable Infrastructure as Code (IaC), build data pipelines and cloud infrastructure, and support feature engineering and deployment of machine learning and AI models. It supports software developers, database architects, data analysts, and data scientists on data initiatives and helps ensure consistent, effective data delivery architecture across ongoing projects. The position is intended to be onsite, now or in the near future, with regular work hours and full days in the office three or more days a week. The manager sets the work schedule and in-office expectations. Available locations are Birmingham, Alabama; Atlanta, Georgia; or Charlotte, North Carolina. The position is exempt from timekeeping requirements under the Fair Labor Standards Act and is not eligible for overtime pay. Regions does not provide relocation assistance and will not sponsor work visas for this position. Applicants must be currently authorized to work in the United States on a full-time basis. The stated target pay range begins at $114,995.65 USD, with a median of $146,400.00 USD. Associates may participate in the Long Term Incentive Plan. Regions offers a flexible and comprehensive benefits package to eligible associates; the listed offerings are summarized below.

Requirements

A Ph.D. and two years of experience in a quantitative, analytical, or STEM field; or a master’s degree and four years of experience in a quantitative, analytical, or STEM field or technical-related field; or a bachelor’s degree and six years of experience in a quantitative, analytical, or STEM field or technical-related field.
Three years of working programming experience in Python, Scala, SQL, and Terraform.
Three years of working experience in cloud-based Big Data technology such as Elastic Map Reduce (EMR), AWS Glue, BigQuery, or Snowflake.

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.
Ability to interpret and ensure compliance with applicable rules, regulations, and industry guidance.
Experience building data solutions at scale.
Experience designing and building relational data structures in multiple environments.
Experience with cloud-based orchestration tools.
Experience with data modeling techniques, including dimensional and time series modeling such as Star Schemas or Data Vault.
Experience with DevOps principles, CI/CD, and the Software Development Lifecycle.
Experience with No-SQL databases.
Experience leading technical projects end to end.
Experience mentoring junior associates on best practices.
Experience working with cloud services at enterprise scale, including data engineering with private networking and zero-trust computing.
A record of delivering operational data solutions, including report- and model-ready data assets.
Significant experience working with senior executives using data, reporting, and visualizations to support strategic and operational decision-making.
Ability to transform and integrate complex data from multiple sources into accessible, understandable, and usable data assets and frameworks.
Strong background synthesizing data and analytics in a large, complex, highly regulated environment.
Strong written and oral presentation skills.
Strong technical background, including database and business intelligence skills.
Experience designing and deploying enterprise-grade generative AI solutions leveraging modern LLMs, preferably with Amazon Bedrock.
Experience developing advanced prompt engineering frameworks incorporating context management, agent orchestration, skills integration, and response evaluation.
Experience implementing AI governance frameworks, including guardrails, compliance controls, and enterprise risk management standards.

Responsibilities

Partner with Regions Technology partners to design, build, and maintain data-based structures and systems supporting Data and Analytics and Data Product use cases.
Assist in building data pipelines to collect and arrange data and manage storage in Regions’ big data environments.
Build robust, testable programs to move, transform, and load data using cloud-based Big Data tools such as Glue, Step-Functions, Snowflake, Kafka, and Sagemaker.
Build applications that integrate with AI, including knowledge base management and document processing.
Ensure data is prepared, arranged, and ready for each defined business use case.
Continuously grow knowledge and skills related to daily tasks.
Ensure compliance with risk management programs, rules and regulations, and cybersecurity practices.
Identify opportunities for and support process improvements.
Apply disciplined change management practices.