We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.
Our disruptor’s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 24 sequential quarters of growth with $436.5M in Q4 FY26 revenue, up 17.4% Y-o-Y growth. Our 26,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We won the 2025 ISG Star of Excellence™ Award for AI and Data Excellence and were named a Leader in the Everest Group Talent Readiness for Next-generation Data, Analytics and AI Services PEAK Matrix® Assessment 2025.
Role: Technology Leader - BFSI (Data &AI)
Location: New Jersey, United States
Travel: Significant client-facing travel expected
About the Role:
The Technology Leader – Data, Analytics & AI is a mission-critical leadership role within our Banking & Financial Services practice. This executive will own the end-to-end vision, strategy, and delivery roadmap for data, analytics, and AI across our banking, capital markets, insurance, and wealth management client portfolio.
The Technology Leader will serve as a trusted advisor to Chief Data Officers, Chief AI officers Chief Risk Officers, Chief Digital Officers, and CTOs at Tier 1 banks, global insurers, asset managers, and payment networks — helping them modernize fragile data estates, meet intensifying regulatory obligations, and unlock commercial advantage through data-driven intelligence. The focus would be on partner platforms e.g. Databricks, Snowflake along with deeper understanding of real-time and batch financial services processes.
Key Responsibilities:
Enterprise Data Strategy for Financial Institutions:
- Define and evolve the BFS-specific data and analytics target-state architecture — spanning retail banking, wholesale/investment banking, insurance, payments, and wealth management business lines.
- Architect multi-year transformation roadmaps that balance regulatory imperatives (BCBS 239, DORA, SR 11-7, GDPR/ CCPA) with commercial data monetization and customer intelligence programs.
- Lead data modernization strategy utilizing platforms such as Databricks, Snowflake for institutions navigating fraud and core banking modernization, post-merger integrations, or cloud adoption, AI enablement programs.
- Lead end-to-end solutioning for complex, multi-geography data programs covering: AI led regulatory data lineage and reporting automation (CCAR, FRTB, LCR, NSFR, AnaCredit), enterprise risk and finance data integration, trade and transaction data platforms, and customer 360 / Know Your Customer (KYC) data products.
- Architect and review platforms e.g. Databricks Lakehouse, cloud data warehouse, and data mesh patterns tailored to BFSI workloads including market data, reference data, instrument master, and high-volume transaction processing.
- Design real-time and near-real-time data pipelines for use cases such as fraud detection, AML transaction monitoring, liquidity risk, and algorithmic trading. Leverage Kafka and other platforms to work on real time.
- Act as a trusted advisor to CDOs, CROs, CFOs, CTOs, and Chief Compliance Officers at financial institutions; lead executive workshops and shape multi-year investment priorities.
- Navigate the intersection of business transformation, technology risk, model risk, and operations within highly regulated, systemically important financial institutions.
- Represent the firm in strategic client conversations, RFPs, and conference/industry forums (e.g., Sibos, Money20/20, GARP, ISDA).
Regulatory Compliance & Risk Data:
- Ensure architecture and delivery align with financial regulatory requirements including BCBS 239 (Risk Data Aggregation), Basel IV, Dodd-Frank, MiFID II/ MiFIR, EMIR, PSD2, DORA, CCAR/DFAST, and applicable central bank reporting mandates.
- Design data governance and lineage frameworks that support regulatory attestation, audit trails, and model risk management (SR 11-7/SS1/23).
- Embed privacy-by-design for PII, financial data, and sensitive customer information across data platforms, with controls for data residency and cross-border transfer requirements.
- Provide technical leadership across cloud-native and hybrid financial data platforms — including AWS, Azure, and GCP — with expertise in platforms such as Snowflake, Databricks, Google BigQuery, and cloud-native data fabric solutions.
- Lead architecture for market and reference data distribution (Bloomberg, Refinitiv, ICE), instrument/entity master data management, and financial messaging standards (FIX, SWIFT, ISO 20022).
- Ensure performance, resilience, cost discipline, and disaster recovery posture commensurate with financial services SLA requirements.
AI, ML & Responsible AI in Financial Services:
- Define the AI/ML enablement strategy — including Generative AI and Agentic AI — on top of trusted financial data foundations; ensure responsible AI governance aligned to ECB/FCA/SEC guidance and internal model risk policy.
- Champion AI use cases with demonstrable ROI: credit decisioning, fraud and AML detection, treasury forecasting, intelligent document processing (KYC/onboarding), and hyper-personalized client advisory.
- Govern model lifecycle management from development through deployment to monitoring, with robust explainability and bias-management controls required by financial regulators.
Data Governance & Operating Model:
- Establish or strengthen enterprise data governance frameworks (ownership, stewardship, quality, lineage, catalog, access controls) aligned to BCBS 239 principles and internal audit requirements.
- Drive adoption of data products and self-serve analytics capabilities across front office (trading, RM/client teams), middle office (risk, compliance, finance), and back-office functions.
- Define data quality metrics and SLAs tied to regulatory reporting accuracy, reducing manual reconciliation and attestation risk.
- Lead strategic pursuits and executive-level proposals for BFS clients; position differentiated data and analytics offerings against Big 4, global SI, and cloud hyperscaler competitors.
- Build relationships with industry bodies, regulators, and FinTech ecosystem partners to stay ahead of market trends and regulatory evolution.
Required Qualifications:
- 20+ years of progressive experience in data and analytics technology leadership, enterprise architecture, and/or large-scale transformation delivery within or serving Banking & Financial Services.
- Deep domain expertise in at least two of: retail/commercial banking, capital markets/ investment banking, insurance, payments, or wealth & asset management.
- Proven track record solutioning and delivering complex, multi-year data programs across geographies, regulators, and C-suite stakeholders at Tier 1 or Tier 2 financial institutions.
- Demonstrable experience with financial regulatory data programs: BCBS 239, CCAR/DFAST, Basel III/IV capital reporting, AML/sanctions data infrastructure, or equivalent.
- Strong executive presence; ability to influence and communicate with C-level stakeholders, Boards, and regulators.
- Deep understanding of modern financial data ecosystems: cloud data platforms, lakehouse/ warehouse architectures, streaming data integration, enterprise data governance, analytics/BI, and AI/ML enablement.
Preferred Experience:
- Direct experience in financial services consulting or advisory within a Tier 1 consulting firm, global SI, or specialist FinTech/ RegTech firm serving BFS clients.
- Experience with AI/ML, Generative AI, and Agentic AI platforms in regulated financial contexts, including model risk management and responsible AI frameworks.
- Exposure to ISO 20022 migration, open banking/PSD2 data strategies, or real-time payments infrastructure.
- Familiarity with market and reference data vendors (Bloomberg, Refinitiv/LSEG, FactSet, ICE) and financial data standards (FIGI, LEI, ISIN, CUSIP).
- Relevant certifications in cloud platforms (AWS/Azure/GCP), data governance (CDMP), or financial risk (FRM, CFA) are advantageous.
Why this Role?
- Global BFS Platform: Shape data strategy for the world's most complex financial institutions across 30+ markets.
- Regulatory & AI Frontier: Work at the convergence of AI innovation and regulatory transformation — the defining challenge in BFS data.
- Thought Leadership: Represent the firm at global industry events; publish IP and frameworks that move the market.
- Impact at Scale: Drive measurable outcomes: faster regulatory reporting, reduced AML false positives, real-time risk visibility.
- Competitive salary and benefits package.
- Culture focused on talent development with quarterly growth opportunities and company-sponsored higher education and certifications.
- Opportunity to work with cutting-edge technologies.
- Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards.