Senior Director Data Engineering Streaming and Platforms

Overview

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.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.

The Director of Data Engineering is accountable for the strategy, delivery, and reliability of the enterprise data engineering platform, with direct leadership responsibility for the Data Streaming Engineering team. This role owns real-time and near-real-time data pipelines, CDC architectures, and event-driven integration patterns that power analytics, operational use cases, and downstream platforms.

You will lead managers and senior engineers responsible for Kafka, Striim and DMS based streaming solutions, while partnering with Architecture, Data Platform, Analytics, and Security leaders to ensure scalable, governed, and production-ready data flows. The role balances people leadership, technical direction, and architectural influence, with selective hands-on engagement for the most complex initiatives.

What You Will Do

• Lead and scale the Data Streaming Engineering organization, including Senior and Lead Data Streaming Engineers
• Own the technical vision and roadmap for real-time and CDC pipelines using Kafka and Striim
• Define standards for streaming architecture, schema evolution, replayability, observability, and operational readiness
• Ensure streaming solutions integrate reliably with Oracle, Postgre
  
  SQL, Amazon Redshift, and Snowflake

• Partner with Enterprise and Data Architects to influence event-driven and hybrid (batch + streaming) platform designs
• Establish approved patterns for:
  • CDC ingestion
  • Event modeling and contracts
  • Topic design and retention
  • Downstream consumption (analytics, APIs, operational systems)
• Guide technology selection and evolution across streaming, orchestration, and cloud-native services

• Hire, develop, and manage high-performing data streaming and data engineering teams (including distributed and offshore teams where applicable)
• Set clear expectations for delivery, quality, reliability, and on-call ownership
• Translate business priorities into executable engineering plans and delivery milestones
• Provide escalation leadership for complex production incidents related to streaming latency, data correctness, or pipeline failures

• Ensure data streaming SLAs/SLOs are defined and met (freshness, latency, completeness)
• Oversee integration of testing, monitoring, and alerting into CI/CD and runtime operations
• Drive continuous improvement in resiliency, scalability, and cost efficiency of streaming platforms

• Collaborate with Analytics, Data Science, Product, and Business stakeholders to align streaming capabilities with business outcomes
• Partner with Security, Governance, and Risk teams to ensure data protection, auditability, and compliance
• Communicate clearly with senior leadership on roadmap progress, risks, and trade-offs

• Bachelor's degree in Computer Science or equivalent experience.
• 12+ years of post-degree professional experience in data engineering or software engineering
• 8+ years in engineering leadership roles, including managing senior engineers and technical leads
• Proven experience building and operating data streaming platforms at scale

• Strong experience with Kafka and/or Striim, including CDC and event-driven architectures
• Experience integrating streaming pipelines with Oracle, Postgre
  
  SQL, Redshift, and Snowflake
• Deep understanding of distributed systems concepts: ordering, fault tolerance, back pressure, and replay
• Hands-on familiarity with cloud-based streaming and data services, especially on AWS

• Strong Python and SQL skills; ability to review and guide complex code and pipeline designs
• Experience with orchestration tools such as Airflow or Argo
• Experience with API-based data integrations and vendor data exchange
• Knowledge of analytics enablement for BI and downstream consumers
• Understanding of core data stewardship processes and data contracts

• Demonstrated success hiring, mentoring, and retaining high-performing engineering teams
• Strong communication skills to influence architecture and delivery across technical and…