Solution Engineering Manager- Financial Data Repository

Citizens • Johnston, RI

2d • Hybrid

About The Position

We are looking for a Solution Engineering Manager to lead a team of engineers in supporting Finance Data Repository (FDR)—the enterprise data backbone powering Treasury, Finance, and Regulatory analytics. This role requires a strategic thinker with strong technical leadership and deep understanding of financial data architecture, Finance, Treasury and Tax functions, regulatory reporting requirements, and modern AI/ML patterns applied to financial data. The ideal candidate bridges the gap between Finance business stakeholders and engineering teams, ensuring solutions are technically sound, regulatory-grade, and aligned with enterprise objectives. The candidate will oversee the end-to-end solution development process—from requirements gathering with Finance and Treasury users, through data model design, pipeline engineering, system integration, AI feature enablement, and post-deployment support. They will work closely with Finance, Technology and vendor teams to ensure FDR solutions are feasible, scalable, and deliver value across the enterprise. They will also play a key role in mentoring and developing the team, fostering a culture of innovation, collaboration, and continuous improvement. The ability to communicate complex financial and technical concepts in a clear and compelling manner will be essential in building trust with business stakeholders, regulators, and engineering partners. Applicants should have a proven profile that combines practitioner depth + cross-finance expertise + technical fluency + AI/ML engineering awareness and translates complex financial behavior into scalable, governed, intelligent data solutions. The Solution Engineering Manager will serve as the primary point of contact between the engineering team and business stakeholders across Finance, and Technology.

Requirements

• Bachelor's degree in Engineering, Computer Science, Finance, or related field
• 10+ years in data engineering, platform engineering, or financial systems integration
• 5+ years in a leadership or management position overseeing engineering teams
• Proven track record delivering complex, multi-system financial data platforms in regulated environments
• 2+ years hands-on experience with AI/ML engineering, data science infrastructure, or intelligent automation in a financial services context
• Strong hands-on experience with Snowflake, Spark, Microservices
• Strong hands-on experience with Data pipeline frameworks (ETL/ELT), cloud data platforms, large-scale data processing
• Strong hands-on experience with Enterprise data architecture patterns (data lake → curated layers → consumption)
• AI/ML Technical Proficiency: LLM orchestration frameworks (LangChain or equivalent)
• AI/ML Technical Proficiency: Vector databases and embedding stores (FAISS, Pinecone, or similar) for RAG and semantic search
• AI/ML Technical Proficiency: ML-driven data quality frameworks and anomaly detection models
• AI/ML Technical Proficiency: Semantic layer design for AI/ML feature consistency and NLQ enablement
• AI/ML Technical Proficiency: Familiarity with cloud AI services (AWS Bedrock, Azure OpenAI, or equivalent)
• Experience with Treasury or financial platforms (QRM)
• Strong working knowledge of ALM, FTP, liquidity management, cash flow modeling
• Strong working knowledge of Interest rate risk concepts (repricing, yield curves, spreads)
• Strong working knowledge of RWA, Economic Capital, and regulatory reporting frameworks
• Strong working knowledge of FR 2052a and capital/liquidity stress testing
• Strong working knowledge of Financial product structures (loans, deposits, derivatives, investment securities)
• Excellent communication and interpersonal skills—ability to translate complex technical, financial, and AI concepts for diverse audiences
• Proven ability to manage multiple projects and competing priorities simultaneously
• Experience working with cross-functional teams across Finance, Risk, Technology, and AI/Data Science organizations
• Strong problem-solving and analytical skills

Responsibilities

• Establish authoritative data models enabling consistency across management and regulatory outputs
• Drive alignment between Finance data domains to support enterprise analytics, reporting, and AI-driven decisioning
• Translate financial concepts into data models and technical solutions; work closely with engineering and data teams
• Engineer data structures and pipelines supporting Finance, Treasury, Insurance, and Tax data
• Design and govern semantic data layers that enable consistent KPI definitions, governed feature reuse across AI/ML models, and natural language query (NLQ) access to finance data
• Architect the data foundation that powers AI use cases across Finance and Treasury, including NLQ / Conversational Analytics, ML-Driven Data Quality & Anomaly Detection, RAG Pipelines & Document Intelligence, AI-Ready Feature Engineering, and Agentic Workflows & Automation
• Partner with the GenAI Council and AI Excellence teams to align FDR data products with enterprise AI roadmap and use case prioritization
• Lead, mentor, and develop a team of data engineers and solution engineers building FDR platform components
• Foster a culture of technical excellence, accountability, and continuous improvement
• Manage capacity planning, resource allocation, and workload balancing across concurrent initiatives
• Upskill team on AI/ML engineering patterns, including vector search, embeddings, LLM integration, and governed feature stores
• Oversee end-to-end design, engineering, and support of the FDR platform
• Translate complex financial business logic into scalable, governed data engineering solutions
• Manage project timelines, resources, and deliverables across concurrent workstreams
• Lead integration with enterprise platforms including Treasury modeling systems (QRM), BI/analytics tools (Power BI, Tableau), and AI/ML serving layers and LLM orchestration frameworks
• Drive modernization from legacy platforms into cloud-native, automated architectures
• Build API-driven and event-based integrations supporting daily and monthly production cycles
• Deliver regulatory-grade datasets supporting internal and external reporting
• Implement source-to-report data lineage, reconciliation logic, and validation frameworks
• Ensure all outputs meet SOX, RDAR, and audit expectations
• Implement within pipelines: data quality monitoring and anomaly detection / reconciliation frameworks (GL, sub-ledger, cross-system balance checks) / full metadata, lineage, and audit traceability
• Ensure AI model outputs are explainable, auditable, and aligned with regulatory expectations
• Align platform outputs to regulatory and internal control standards
• Partner with Treasury, Finance, Tax, and Technology to define requirements, assess feasibility, and ensure scalability
• Present solutions and progress to senior leadership and regulatory stakeholders
• Support pre-implementation activities including vendor evaluation, competitive analysis, and solution demonstrations
• Continuously refine engineering processes, methodologies, and tools to enhance delivery efficiency, data quality, and platform reliability
• Stay current with industry trends, emerging technologies, AI/ML advancements, and cloud/enterprise data platforms

Benefits

• Equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague’s or a dependent’s reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws.
• Fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism.
• Employment decisions are based solely on merit, qualifications, performance and capability.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager