Engineer Data

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

This role supports Empower’s data and AI strategy, with a focus on building Responsible AI capabilities. The Data Engineer will design and implement scalable, ethical, and secure data pipelines and infrastructure that underpin AI/ML systems, ensuring high-quality data flows into model development, testing, monitoring, and governance workflows. The candidate will work across cloud (AWS) and on-premises environments, contributing to the lifecycle of data used for Responsible AI tooling, including bias detection, model transparency, and compliance tracking. 

ESSENTIAL FUNCTIONS: 

• Design, build, and maintain data pipelines that support model development, testing, and monitoring, with a focus on AI governance and traceability. 

• Collaborate with cross-functional teams (including Data Scientists, ML Engineers, and Risk) to understand data needs for AI use cases. 

• Integrate data quality, lineage, and metadata tracking into ETL pipelines to support Responsible AI workflows. 

• Support ingestion and transformation of structured and unstructured data (including NLP datasets) for AI model training and evaluation. 

• Design with compliance in mind: integrate secure handling of PII and support auditability in data flows. 

• Participate in technical design discussions focused on enabling transparency, fairness, and explainability in data workflows. 

• Troubleshoot and resolve performance and data quality issues in distributed AI pipelines. 

• Contribute to reusable libraries or templates to support standardized data practices across AI projects. 

QUALIFICATIONS: 

• Bachelor’s Degree in Computer Science, Information Systems, or related field. 

• 2–6 years of experience in data engineering, preferably in AI/ML environments. 

• Strong Python and SQL skills with experience in data pipeline orchestration (e.g., Airflow, Step Functions). 

• Experience with Big Data frameworks (e.g., Spark, Hadoop) and streaming data platforms (e.g., Kafka). 

• Experience working in AWS environments with services like S3, Glue, Redshift, SageMaker, and Lake Formation. 

• Familiarity with machine learning workflows and data requirements (e.g., training/test splits, data versioning, feature stores). 

• Experience integrating data validation, data lineage, or metadata tools (e.g., Great Expectations, Apache Atlas, Amundsen). 

• Understanding of Responsible AI principles and experience supporting data aspects of fairness, bias, explainability, or model monitoring is a strong plus. 

• Experience with JIRA and Agile methodologies. 

• Experience in financial services or other highly regulated environments preferred. 

This job description is not intended to be an exhaustive list of all duties, responsibilities and qualifications of the job.  The employer has the right to revise this job description at any time.   You will be evaluated in part based on your performance of the responsibilities and/or tasks listed in this job description.   You may be required perform other duties that are not included on this job description.  The job description is not a contract for employment, and either you or the employer may terminate employment at any time, for any reason.

We are an equal opportunity employer with a commitment to diversity.  All individuals, regardless of personal characteristics, are encouraged to apply.  All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.