Cloud Data Engineer - AI Platform

Regions Bank•Atlanta, GA

2d•$114,996 - $146,400•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. Working on cross-functional teams, this role develops reusable Infrastructure as Code (IaC) to build data pipelines and cloud infrastructure, and supports feature engineering and deployment of machine learning and artificial intelligence models. The role supports software developers, database architects, data analysts, and data scientists on data initiatives and helps ensure consistent, optimal data delivery architecture across ongoing projects. The position builds data structures and systems, manages data collection and storage in Regions’ big data environments, and develops robust programs for moving, transforming, and loading data using cloud-based big data tools. It also builds applications that integrate with AI, including knowledge base management and document processing, and prepares data for defined business use cases. The position is intended to be onsite now or in the near future, with full days in the office three or more days a week; the manager sets the work schedule and in-office expectations. Locations available for the role are Birmingham, Alabama; Atlanta, Georgia; or Charlotte, North Carolina. The listed location is Riverchase Operations Center in Hoover, Alabama. Relocation assistance and work visa sponsorship are not provided. The position is exempt from FLSA timekeeping requirements and is not eligible for overtime pay.

Requirements

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 MapReduce (EMR), AWS Glue, BigQuery, or Snowflake.
Ability to interpret and ensure compliance with applicable rules, regulations, and industry guidance.
Experience building data solutions at scale.
Experience with cloud technologies and migrations.
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 NoSQL databases.
Experience leading technical projects from end to end.
Experience mentoring junior associates on best practices, with helping and teaching expected.
Experience working with enterprise-scale cloud services, including data engineering with private networking and zero-trust computing.
Record 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.
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 communication skills, including presentations.
Strong technical background, including database and business intelligence skills.
Must currently be authorized to work in the United States on a full-time basis; Regions will not sponsor work visas for this position.

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 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 data storage in Regions’ big data environments.
Build robust, testable programs for moving, transforming, and loading 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 seek opportunities to grow knowledge and skills related to daily tasks.
Ensure compliance with risk management programs, rules and regulations, and cybersecurity practices.
Identify and support process improvements.
Apply disciplined change management practices.