Senior Director, Data Engineering & Governance

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 Functions

Data 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

Qualifications

Required

• 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