Principal Engineer, Software

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🕒 July 10

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Empower

WebsiteLinkedInAll Job Openings

10,000+ employees

💸 Finance

💳 Fintech

👥 B2C

Finance • Fintech • B2C

Empower is a leading provider of financial services focused on helping individuals and organizations achieve financial freedom through retirement planning and investment management. Serving over 19 million Americans, Empower offers a comprehensive suite of finance-related services, including smart planning and investment advice, and tools like the Empower Personal Dashboard™ for a complete financial view. The company is renowned as a top retirement plan provider and works closely with personal investors, workplace plan savers, plan sponsors, and financial professionals. Empower is also recognized for initiatives in Diversity, Equity, Inclusion, and has a social commitment that bolsters community impact.

📋 Description

• Provides technical leadership across the design, development, modernization, and operation of enterprise data platforms and analytics solutions • Defines scalable data engineering patterns • Leads complex data integration and transformation initiatives • Enables reliable, governed, and high-performing data products that support business reporting, analytics, and advanced AI/ML use cases • Works closely with data analysts, data engineers, business stakeholders, architects, product owners, and technology partners to translate business needs into resilient data solutions • Serves as a senior technical expert and mentor, helping the team modernize from legacy reporting and ETL platforms toward cloud-native, automated, and analytics-ready data architecture • Leads the design and implementation of scalable data engineering solutions, including data pipelines, data models, data integrations, and analytics-ready data products • Provides technical leadership for data architecture, ETL/ELT design, code reviews, performance tuning, production support, and issue resolution • Guides modernization of legacy data and reporting platforms, including migration from traditional ETL and reporting tools to modern cloud data platforms and transformation frameworks • Designs and oversees data pipelines using cloud-based technologies, Python, Spark, SQL, and related orchestration and transformation tools • Supports enterprise analytics platforms, including data warehouse, reporting, semantic layer, and business intelligence environments • Partners with stakeholders to define and execute the technical roadmap for data engineering, analytics enablement, platform modernization, data quality, and automation • Establishes and promotes engineering standards, reusable patterns, coding guidelines, testing practices, data quality controls, and documentation expectations • Collaborates with architecture, security, infrastructure, governance, and business teams to ensure data solutions are secure, reliable, scalable, and aligned to enterprise standards • Mentors engineers and technical team members, supporting skill development in cloud data engineering, data modeling, analytics engineering, and modern data platform practices • Contributes to 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 • Stays informed about emerging data engineering, cloud, analytics, AI/ML, and automation trends to drive continuous improvement and technical innovation

🎯 Requirements

• Bachelor’s degree in computer science, information systems, data engineering, analytics, engineering, or equivalent training and experience • 12+ 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/ELT development; experience with Spark or similar large-scale data processing frameworks strongly preferred • Experience with cloud-based data platforms and services, preferably AWS, including development, deployment, monitoring, and operational support of data solutions • Experience with enterprise data warehouses, data marts, reporting platforms, and business intelligence solutions; familiarity with platforms such as Redshift, Snowflake, SAP BusinessObjects Data Services, SAP Web Intelligence, or similar technologies preferred • Experience with modern data transformation and analytics engineering tools such as dbt or equivalent frameworks preferred • 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 team player with the ability to mentor technical team members and influence engineering direction across teams • Cloud, data engineering, data architecture, analytics engineering, or AI/ML certifications preferred

🏖️ Benefits

• Flexible work environment • Internal mobility • Commitment to purpose and well-being • Work-life balance • Inclusive environment