Director, Data Management

We’re looking for talented professionals to join us in bringing smart money management and payment solutions to everyone’s fingertips. This position is classified as structured hybrid, with an expectation of a minimum of three (3) days per week working in the office and flexibility to work remotely on the remaining days. On‑site expectations may evolve over time to support business needs, with clear communication provided in advance.

This position is open only to candidates who currently reside in one of the following approved locations:
Los Angeles, CA

Green Dot is seeking a strategic and execution-focused Engineering Leader to lead the enterprise‑wide data warehousing practice. This role will be responsible for leading the engineering aspect of data warehouse initiatives across all business units in terms of design, development and quality making sure the practice adheres to data governance. This position also leads the Data Governance practice and AI drive in the data spaces leveraging AWS Redshift, Informatica and Claude AI.

It also defines data security and adheres to compliance rigors across data needs for all business units. You will partner closely with Technology, Risk, Compliance, and Product teams to drive data quality, lineage, and stewardship initiatives that support regulatory obligations and business growth.

Lead the design, development and optimization of data warehouse solutions using AWS Redshift. Define and execute the enterprise data strategy, architecture roadmap and modernization initiatives. Architecting and maintaining Operational data stores (ODS), Enterprise Data Warehouse (EDW) and associated data intelligence environments including data lakes, data marts, and metadata repositories. Designing and implementing high performance data movement pipelines using multiple ETL tools (Informatica, Azure Data Factory, SQL Packages, etc) with batch and real‑time event data streams leveraging Informatica IDMC.

Ensure high availability, performance tuning, Scalability and reliability of data platforms and pipelines. Developing scalable and re‑usable frameworks for ingestion of structured and semi‑structured data; and implementing various large‑scale settlement and reconciliation frameworks. Designing and creating data architecture and data flow diagrams and collaborating with peers to translate requirements into logical and physical data models. Ensures data warehouse features and capabilities are incorporated into data model designs to optimize performance, resiliency, and scalability.

Delivering and presenting proofs of concept to of key technology components to project stakeholders and internal technology leaders. Leading and coordinating the design and operationalization of Data Governance capabilities like – data lineage, data catalog, data quality, etc. Problem‑solving of Data warehouse and ODS application issues and production errors, including high level critical production issues that require immediate attention. Write, test and produce production grade ETL data pipeline code in financial services without relying on testing by other groups.

Implement intelligent testing frameworks that auto‑generate test cases, predict bugs, and enable self‑healing. Leads the creation of test strategy, test planning, and test execution related to all aspects of testing like functional, integration, systems, end‑to‑end testing, accessibility, database validations, and automation. Integrate test suites into CI/CD pipelines (Jenkins, Github). Metadata & Lineage Management:
Oversee the implementation of tools and processes for metadata capture, data lineage tracking, and cataloging. Ensures data quality, completeness and consistency through carious…