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