Principal Data Engineer

Empower Retirement, LLC is focused on transforming financial lives with a flexible work environment and opportunities for internal mobility. The Principal Data Engineer will provide technical leadership in designing and developing enterprise data platforms and analytics solutions, ensuring reliable and governed data products that support business reporting and advanced AI/ML use cases.

Responsibilities:

• Provide technical feasibility analysis and solution evaluation for data and analytics initiatives based on business, operational, and regulatory needs
• Lead the design and implementation of scalable data engineering solutions, including data pipelines, data models, data integrations, and analytics-ready data products
• Provide technical leadership for data architecture, ETL and ELT design, code reviews, performance tuning, production support, and issue resolution
• Guide the modernization of legacy data and reporting platforms, including migration from traditional ETL and reporting tools to modern cloud data platforms and transformation frameworks
• Design and oversee data pipelines using cloud-based technologies, Python, Spark, SQL, and related orchestration and transformation tools
• Support enterprise analytics platforms, including data warehouse, reporting, semantic layer, and business intelligence environments
• Partner with data analysts, data engineers, business stakeholders, architects, product owners, and technology partners to translate business needs into resilient data solutions
• Define and execute the technical roadmap for data engineering, analytics enablement, platform modernization, data quality, and automation
• Establish and promote engineering standards, reusable patterns, coding guidelines, testing practices, data quality controls, and documentation expectations
• Collaborate with architecture, security, infrastructure, governance, and business teams to ensure data solutions are secure, reliable, scalable, and aligned with enterprise standards
• Mentor engineers and technical team members, supporting skill development in cloud data engineering, data modeling, analytics engineering, and modern data platform practices
• Support AI/ML enablement by ensuring data pipelines, curated datasets, and feature-ready data assets are reliable, governed, and suitable for advanced analytics and machine learning use cases
• Stay informed about emerging trends in data engineering, cloud, analytics, AI/ML, and automation to support continuous improvement and technical innovation

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Analytics, Engineering, or equivalent training and experience
• 12 or more years of experience in software engineering, data engineering, analytics engineering, or enterprise data platform development
• Proven experience designing, developing, and maintaining complex data solutions involving multiple systems, stakeholders, business domains, and production dependencies
• Strong experience with Python, SQL, distributed data processing, and ETL and ELT development
• Experience with cloud-based data platforms and services, including development, deployment, monitoring, and operational support of data solutions
• Strong understanding of data modeling, data warehousing, data quality, metadata management, data lineage, performance optimization, and production support practices
• Working knowledge of AI/ML concepts and the data engineering practices required to support advanced analytics, machine learning, and model-ready datasets
• Proven ability to design data solutions that integrate with internal and external systems while meeting security, governance, scalability, and reliability requirements
• Deep understanding of software development and data engineering practices in a distributed team environment, including version control, testing, CI/CD, release management, and operational monitoring
• Excellent problem-solving, analytical, communication, and stakeholder management skills
• Proven ability to collaborate effectively, mentor technical team members, and influence engineering direction across teams
• Experience with Spark or a similar large-scale data processing framework
• Experience with AWS cloud data platforms and services
• Experience with enterprise data warehouses, data marts, reporting platforms, and business intelligence solutions
• Familiarity with Redshift, Snowflake, SAP BusinessObjects Data Services, SAP Web Intelligence, or similar technologies
• Experience with modern data transformation and analytics engineering tools such as dbt or equivalent frameworks
• Cloud, data engineering, data architecture, analytics engineering, or AI/ML certifications
• Experience with a technology environment that includes AWS, Python, Spark, SQL, Redshift, SAP BusinessObjects Data Services, SAP Web Intelligence or Reports, dbt, Snowflake, and related data engineering, reporting, and orchestration platforms