The Director of Data Engineering & Governance leads the technical foundation and strategic governance of Fintech's enterprise data ecosystem. This role owns the full lifecycle of data infrastructure across cloud-native platforms, while building and operationalizing the governance framework that ensures data quality, security, and compliance across 12 product lines processing $55B+ in annual regulated payments.
Reporting to the VP of Data & AI, this Director manages a team of Data Engineers and Database Administrators, chairs the cross-functional Data Governance Council, and partners across Products, Infrastructure, Legal, and Compliance to position data as a strategic enterprise asset. The role is critical to Fintech's continued platform evolution, regulatory compliance posture, and AI readiness.
Essential FunctionsData Engineering Leadership & Team Management- Lead, mentor, and develop a team of Data Engineers and Database Administrators responsible for Fintech's data infrastructure
- Drive technical excellence in data engineering practices, establishing coding standards, review processes, and operational runbooks
- Manage capacity planning, project prioritization, and resource allocation across concurrent initiatives including platform evolution, product delivery, and operational maintenance
- Build a high-performing, collaborative team culture aligned with Fintech's collective intelligence philosophy
Database Operations & Platform Management- Oversee operations and optimization of the enterprise database portfolio:
- PostgreSQL: Primary transactional database supporting modernized applications
- Apache Druid: Real-time analytics and OLAP workloads
- MongoDB: Document store for flexible schema requirements
- OpenSearch: Search, logging, and observability
- Establish database performance monitoring, capacity management, and incident response procedures
- Drive continuous optimization of cloud-native database deployments for cost, performance, and reliability
- Partner with Infrastructure (Remya) on Azure cloud optimization, Kubernetes deployment patterns, and Terraform infrastructure-as-code for data resources
Data Pipeline Architecture & Operations- Own the design, development, and maintenance of enterprise data pipelines spanning:
- Ingestion: Apache NiFi for batch/file processing, SFTP integrations with trading partners
- Streaming: Apache Kafka for real-time event pipelines
- Processing & Storage: Databricks lakehouse as the enterprise source of truth with Unity Catalog governance
- Distribution: Pipelines feeding fit-for-purpose downstream databases and third-party integrations (Salesforce, HubSpot, Chameleon, Heap)
- Establish pipeline observability, alerting, and SLA management across the data stack
- Drive adoption of DataOps practices including CI/CD for data pipelines, automated testing, and deployment automation
Data Contracts & API Development- Define and implement the enterprise data contract framework-formalizing schemas, quality expectations, SLAs, and ownership for data exchanged between producers and consumers
- Partner with API/MDM team (Ashin) to design and deliver data APIs via KrakenD gateway, ensuring consistent access patterns and rate limiting
- Establish schema registry and versioning practices for Kafka topics and Databricks tables
- Integrate data contracts into the SDLC, ensuring contract validation at pipeline deployment
Data Governance Program Leadership- Establish and chair the enterprise Data Governance Council with representation from Data, Products, Infrastructure, Legal, and Compliance
- Design and operationalize the enterprise data governance framework grounded in DAMA DMBOK, covering:
- Data quality standards and measurement
- Data classification and sensitivity labeling
- Access control policies and enforcement
- Retention and archival requirements
- Lineage and impact analysis
- Implement governance controls natively within Databricks Unity Catalog-including catalog/schema/table permissions, row/column-level security, and attribute-based access via integration with CRAFT (zero-trust ABAC layer)
- Lead metadata management using Open Metadata integrated with Unity Catalog, ensuring comprehensive lineage from source systems through consumption
- Maintain the enterprise business glossary with consistent definitions across all 12 product lines
- Recruit and coordinate federated Data Stewards and Data Owners across business units
Data Security & Protection- Own the data security posture across the enterprise data platform, partnering with Information Security to implement defense-in-depth controls
- Implement and monitor data-at-rest encryption (Azure Storage encryption, Databricks workspace encryption) and data-in-transit encryption (TLS for all data movement)
- Establish data masking, tokenization, and anonymization standards for sensitive data elements (PII, PCI, financial data)
- Configure and maintain Unity Catalog audit logging and system tables for comprehensive data access monitoring
- Define and enforce least-privilege access models across all data platforms, integrating with Auth0 identity and OPA policy enforcement
- Lead data security incident response procedures, including breach investigation, impact assessment, and remediation
- Conduct periodic data security risk assessments and vulnerability remediation
Certification, Audit & Regulatory Compliance- Serve as the data engineering and governance lead for SOC 2 Type II certification, ensuring data-related controls are documented, implemented, tested, and auditable
- Align governance and security controls with NIST Cybersecurity Framework (CSF 2.0), particularly:
- Govern: Risk management strategy, roles/responsibilities, policy
- Identify: Asset management, data inventory
- Protect: Data security, access control, platform security
- Detect: Continuous monitoring via Unity Catalog audit logs
- Prepare governance documentation and evidence collection for NYDFS Cybersecurity Regulation (23 NYCRR 500) requirements-access controls, audit trails, third-party data risk management, and incident reporting
- Ensure CCPA compliance through governance processes supporting data subject rights (access, deletion, portability) with technical implementation in the data platform
- Partner with Legal on 50-state alcohol regulatory data requirements, ensuring proper retention and auditability for licensing compliance
- Conduct annual data governance maturity assessments and develop continuous improvement roadmaps
AI & Advanced Analytics Enablement- Establish data engineering and governance foundations for Fintech's AI platform including:
- Training data lineage and provenance documentation
- Feature store governance and access controls
- Model input/output data quality monitoring
- Partner with Data Architecture on vector and graph database integration patterns for AI workloads
- Monitor evolving AI governance requirements (NIST AI RMF, SEC AI disclosure guidance, NYDFS AI risk guidance) and advise council on data governance implications
- Ensure AI training data complies with data classification, consent, and regulatory constraints
Strategic Planning & Stakeholder Engagement- Develop and execute the multi-year data engineering and governance roadmap aligned with Fintech's platform strategy and 3-year ecosystem vision
- Translate technical data initiatives into business value for executive stakeholders
- Manage vendor relationships for data platform tooling (Databricks, Confluent/Kafka, OpenMetadata)
- Represent Data Engineering & Governance in cross-functional initiatives including M&A integration, new product launches, and enterprise architecture reviews
QualificationsRequired- 10+ years of progressive experience in data engineering, data management, or related technical disciplines
- 5+ years of direct people management experience leading data engineering or database administration teams
- 3+ years of hands-on experience building and operationalizing data governance programs
- Deep technical expertise with modern data platforms:
- Lakehouse: Databricks (Unity Catalog, Delta Lake, Spark)
- Streaming: Apache Kafka (or Confluent), event-driven architectures
- Databases: PostgreSQL, MongoDB, and at least one analytical database (Druid, ClickHouse, or similar)
- Orchestration/Ingestion: Apache NiFi, Airflow, or comparable tools
- Experience implementing data governance controls in cloud-native environments, including role-based and attribute-based access control
- Working knowledge of compliance frameworks: SOC 2, PCI-DSS, and data privacy regulations (CCPA, GDPR)
- Demonstrated ability to lead cross-functional governance bodies and drive outcomes through influence
- Strong communication skills with ability to translate technical concepts for business and executive audiences
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
Preferred- Experience with data security practices: encryption, tokenization, masking, DLP, and security monitoring
- Familiarity with cybersecurity frameworks (NIST CSF, NIST 800-53) and security audit processes
- Experience with metadata management and data lineage tools (OpenMetadata, Atlan, Alation, or Collibra)
- Knowledge of API gateway patterns and data API design (REST, GraphQL)
- DAMA CDMP, CISM, CISSP, or equivalent certifications
- Experience in payments, fintech, or regulated industries (alcohol beverage compliance a plus)
- Experience supporting AI/ML data pipelines and governance
- Master's degree in relevant discipline
Excellent to Have- Direct experience with NYDFS Cybersecurity Regulation (23 NYCRR 500) compliance
- Background in cybersecurity operations, security architecture, or security engineering
- Experience implementing zero-trust data access models
- Familiarity with data security tools: SIEM integration, data loss prevention, privileged access management
