Empower

Director

• Define and own the data product strategy and operating model.
• Establish and manage domain-based data product portfolios, including customer, transaction, risk, and operations domains.
• Translate enterprise strategy into multi-year data product roadmaps supported by clearly defined value cases.
• Lead, mentor, and scale a team of Data Product Managers.
• Oversee delivery of complex, cross-domain data products and data platforms.
• Partner with Data Governance, Risk, Legal, and Compliance teams to embed controls within data products.
• Serve as a trusted advisor to senior business and technology leaders.
• Define success metrics for data products, including adoption, data quality, and business impact.

Director, Data Products – Strategy

Customer Support

• Resolve client, advisor, and internal support inquiries submitted through Zendesk
• Partner with engineering teams and third‑party aggregators to identify, escalate, and resolve technical issues
• Analyze trends in client issues and serve as the voice of the customer to drive product improvements
• Create and maintain Help Center articles and technical documentation for common issues
• Recommend and support process and tooling improvements to enhance customer satisfaction

Technical Support Specialist, Aggregation

Data Engineer

• Lead a team of data engineers transforming data from disparate systems to enable insights and analytics for business stakeholders.
• Create technical roadmaps and recommend strategies for data pipelines and integration.
• Leverage cloud-based infrastructure to implement scalable, resilient, and efficient data engineering solutions.
• Collaborate with data analysts, data scientists, database administrators, cross-functional teams, and business stakeholders to solve problems.
• Influence architectural decisions and design patterns across the data platform.
• Provide technical leadership across the software development lifecycle, from design to deployment, including hands-on contribution.
• Develop project plans, facilitate prioritization timelines, allocate resources, and take ownership of assigned technical projects in a fast-paced environment.
• Perform code reviews and ensure data engineers follow best-practice coding standards.
• Define and validate test cases to ensure data quality, reliability, and a high level of confidence.
• Continuously improve quality, efficiency, and scalability of data pipelines, reducing gaps and inconsistencies.

Director, Data Engineering – Automation

Full-stack Engineer

• Design and execute adversarial testing strategies for AI and GenAI systems, including jailbreaks, prompt injection, unsafe completions, and ungrounded responses.
• Build and maintain automated red-team testing frameworks, evaluation harnesses, and adversarial test suites.
• Analyze model and system behavior to identify safety, robustness, and security vulnerabilities.
• Document findings and provide clear, actionable remediation guidance to application and platform teams.
• Partner with AI/ML engineers to harden applications and workflows based on red-team findings.
• Collaborate with QA to integrate adversarial testing into continuous validation and release pipelines.
• Coordinate with Security teams on LLM threat modeling, vulnerability escalation, and incident support when safety failures occur.
• Contribute to research and prototyping of new adversarial testing techniques and red-team tooling.

Senior Engineer, AI/ML – Responsible AI Red Team

Systems Engineer

• Coordinate cross-team workflows, dependencies, and delivery sequencing across multiple organizations.
• Manage and maintain Kanban-based workflows using tools such as Jira to track initiatives, risks, and dependencies.
• Maintain operational artifacts including documentation hubs, decision records, evaluation inventories, and knowledge repositories.
• Translate complex technical and analytical outputs into structured materials for leadership reviews, governance processes, and audits.
• Support vendor engagements related to tools, services, or research partnerships, including coordination and follow-up tracking.
• Perform analytical work to assess adoption, operational performance, and resourcing needs.
• Support planning and coordination of internal symposiums, showcases, and cross-functional knowledge-sharing events.

Principal Business Systems Analyst, AI/ML

Data Scientist

• Lead evaluation and validation of AI and GenAI systems, including assessment of hallucination, fairness, robustness, explainability, and other model behavior risks.
• Design and implement repeatable evaluation workflows, benchmark datasets, and structured model behavior tests.
• Serve as the Responsible AI data science partner for assigned AI delivery teams, guiding the integration of RAI metrics, guardrails, and evaluation practices.
• Translate research findings and experimental methods into scalable, platform-ready evaluation capabilities.
• Collaborate with AI/ML engineers and QA analysts to align evaluation logic with testing pipelines and deployment workflows.
• Support the creation of model cards, evaluation documentation, and transparency artifacts required for governance and review.
• Provide Responsible AI consultation to product, engineering, risk, legal, and governance stakeholders.
• Mentor junior and mid-level data scientists on evaluation design, experimental rigor, and Responsible AI practices.

Senior Data Scientist, Responsible AI

Manager

• Lead Advisory Performance & Client Outcomes
• Directly lead a team of 12–15 licensed Financial Advisors delivering retirement-focused advice to participants through inbound client interactions
• Drive performance across key advisory metrics including planning conversations, client experience (NPS), productivity, and quality outcomes
• Ensure consistent delivery of high-quality, compliant, and client-centric advice that improves retirement readiness
• Establish a strong coaching culture focused on behavior change, skill development, and performance improvement
• Develop advisors’ financial planning knowledge and readiness for advancement into senior advisor, specialist, or leadership roles
• Act in a Series 24 supervisory role, including oversight of account opening for taxable accounts and brokerage IRAs
• Approval and supervision of fiduciary contracts and best-interest advice
• Monitor daily queue performance and allocate resources to maintain contractual service-level agreements (SLAs)

Senior Manager – Advisory Services

Financial Planning and Analysis

• Educate retail clients on the Advisory Services available through their plan to reach their retirement goals
• Possess knowledge of the clients' financial goals and be able to explain managed account service offerings
• Adhere to compliance/risk procedures and exhibit detailed attention to policy and procedures by focusing on the client's best interest
• Will perform aspects of financial planning for customer
• Perform mutual fund, equity, bond, ETF, Muni and, CD trades
• Uncover leads and opportunities to hand off to the Wealth Advisor Team
• Drive new business opportunities
• Deliver an efficient and responsive client experience by taking ownership, delivering accurate information, and initiating proactive follow up

Investment Advisor

• Lead, develop, and retain a high-performing architecture team through hiring, coaching, performance management, and career development
• Establish role clarity, expectations, and growth paths for architects, ensuring consistent practice maturity and strong engagement
• Define and evolve current-state and target-state architectures aligned to business strategy, regulatory expectations, and long-term sustainability
• Establish and maintain enterprise and domain reference architectures, standards, and guiding principles that enable consistent solution design
• Lead architectural governance processes, including architecture reviews, decision records, and lifecycle guidance for technology adoption and retirement
• Ensure architectural components and standards are fully documented, including value proposition, current and target state, operational considerations, KPIs, and decision rationale
• Enable delivery teams through reusable patterns, templates, guardrails, and clear architectural guidance that reduces friction and rework
• Provide architectural leadership across data architecture, data management, data security, data delivery, advanced analytics enablement, and business architecture alignment
• Partner with engineering, product, infrastructure, security, risk, and business stakeholders to align architecture decisions with delivery and operational outcomes
• Drive modernization efforts that reduce technical debt, simplify integrations, and improve system resilience and scalability
• Guide API-first and event-driven integration approaches that improve reuse, consistency, and observability
• Promote security, privacy, and resiliency by design through architectural standards and review practices
• Support cloud maturity through cost-aware, operationally sound architecture decisions and platform enablement
• Evaluate emerging technologies and innovation opportunities, converting successful proofs into scalable, governed capabilities
• Plan and manage team capacity, prioritization, and investment alignment to meet strategic objectives and delivery commitments

Senior Director of Data Architecture

Backend Engineer

• Lead the design and development of microservices-based architectures using Spring and Spring Boot.
• Architect and build real-time streaming applications using Apache Kafka.
• Define technical strategy and oversee the full software development lifecycle, from requirements to deployment.
• Mentor and guide engineers, conducting design and code reviews to ensure high standards.
• Champion TDD and BDD practices, ensuring code quality and maintainability.
• Collaborate with cross-functional teams to deliver secure, reliable, and scalable software.
• Drive adoption of best practices in system design, testing, DevOps, and CI/CD pipelines.
• Optimize performance of applications and resolve complex technical issues.
• Ensure systems are built for high availability, scalability, and maintainability.
• Contribute to architectural decisions and align technical initiatives with business goals.

Lead Software Engineer - Java

• Lead cross-functional collaboration in an Agile environment to gather, document, and manage requirements for software development projects
• Translate business needs into user stories and supporting artifacts, ensuring alignment with project goals and shared understanding across stakeholders and development teams
• Conduct complex analysis of current systems and processes to identify improvement opportunities, efficiency gains, and impacts of change
• Partner with Engineers and Quality Assurance to review requirements, validate functionality, and support delivery outcomes
• Troubleshoot issues, conduct impact analysis, recommend solutions, and support business queries, particularly during major incidents
• Review and socialize system enhancements with project stakeholders, ensuring solutions align with high-level technology and organizational objectives
• Create and maintain documentation such as flow diagrams, workflows, specifications, reports, and manuals outlining system and technical solutions
• Coach and mentor other Analysts; lead the COE for the Analyst community within the value stream
• Collaborate with Architects and System Analysts to solve complex business problems and contribute to future application roadmaps focused on scalability and resiliency
• Stay informed on best practices and emerging trends in business analysis and Agile methodologies, influencing discipline standards and practices

Principal Business Systems Analyst

• Provide technical feasibility and evaluation of the product based on the business needs
• Provide technical leadership to the team in design finalization, code reviews, and resolving production support and maintenance issues
• Lead design and implementation of critical software components and systems
• Mentor technical members of the team
• Contribute to the development of coding standards, best practices, and guidelines
• Collaborate with stakeholders to define and execute the technical roadmap
• Stay informed about emerging technologies and industry trends to drive technical innovation
• Hands-on role which involves coding on day-to-day basis
• Lead domain modelling designs
• Responsible for production on-call duties like any other team member
• Produce high quality design documentation

Principal Software Engineer

Principal Software Engineer – Java

Risk

• Own the enterprise data governance and knowledge management strategy and execution across structured and unstructured data.
• Run the governance framework and operating model (policies, standards, RACI; DCAM/DAMA-aligned), steward network, and committee cadence; embed governance checkpoints into the data-product lifecycle and portfolio processes.
• Operationalize privacy, retention, and records controls for CCPA/GLBA, ERISA retention, and broker-dealer books and records requirements (for example, SEC 17a-4/FINRA), with auditable processes and platform guardrails (legal hold, WORM/immutability where required).
• Scale metadata, catalog, and lineage capabilities: business glossary, CDE lifecycle, technical lineage, and catalog adoption (for example, Collibra); set enterprise metadata standards and exchange patterns across platforms and APIs.
• Establish enterprise data quality and observability standards, SLAs, issue management, and monitoring; integrate data quality signals into stewardship workflows and EDAC scorecards.
• Govern unstructured content (docs, wikis, PDFs) including taxonomy and ontology/knowledge graph patterns and a “trusted knowledge” certification process; partner with Enterprise AI engineering to govern unstructured data as a first-class citizen.
• Define API and data-sharing standards for publication and consumption, ensuring consistent semantics, authorization, and lineage.
• Partner with Risk, Legal, and responsible AI teams to extend governance to AI, including model inventory, usage policies, transparency and bias testing, and GenAI data-use controls.
• Lead executive engagement and change: present posture and KPIs, secure funding, and run training, communications, and adoption.
• Drive value realization through a published governance scorecard and targeted 12-month outcomes (for example: priority CDE coverage, catalog and glossary adoption, audit evidence packages, and reduced data quality issue closure time).

Senior Director of Data Governance, Knowledge Management

• Lead the enterprise data architecture function, including hiring, developing, and retaining architecture talent, and setting expectations for how architecture work is produced, reviewed, and adopted across delivery organizations.
• Own Empower’s enterprise data architecture strategy and direction and hold the organization accountable for maintaining the target state, roadmaps, and guidance needed to execute modernization priorities.
• Direct the architecture team’s definition of enterprise patterns for data movement, processing, storage, and consumption across operational, analytical, and advanced analytics/AI use cases.
• Communicate enterprise data architecture direction to executives and delivery leaders, making tradeoffs explicit (risk, cost, stability, speed) and driving decisions that improve outcomes.
• Sponsor and oversee modernization of legacy data capabilities, ensuring the team drives migration sequencing, platform evolution guidance, and decommissioning plans that reduce complexity and technical debt.
• Partner with platform leadership to advance AWS-based cloud maturity and scalable platform patterns, ensuring the architecture team provides guardrails that enable automation, repeatability, and delivery speed.
• Own the enterprise approach to integration evolution and reusable integration capabilities, ensuring the team reduces point-to-point complexity and improves enterprise data access through consistent patterns.
• Ensure the team defines and drives API-first and event-driven patterns (including streaming where appropriate), with clear expectations for latency, scalability, resiliency, and consumer experience.
• Promotes the creation of architecture that conforms to enterprise standards.
• Oversee the definition of enterprise consumption standards across BI/reporting, APIs/data services, and analytics workbenches, including performance practices, traceability, and compliance/audit readiness.
• Sponsor architectural direction for ETL/ELT performance and cost optimization, ensuring the team establishes practices for tuning, workload design, capacity planning, and pipeline reliability instrumentation.
• Establish an architecture engagement model and operating rhythm that provides timely guidance and reduces late-cycle rework.