Green Dot Corporation

Green Dot Corporation

Director, Data Management

US-CA California Los Angeles/Orange County Home Office · Director · Full-time

No sponsorship$180k-$260kDetected 51 days ago
PythonGitSQLRedshiftAWSAzureCloud PlatformsCI/CDGitHub ActionsJenkinsData AnalysisData EngineeringLLMsComplianceAccessibilityStakeholder ManagementLeadershipCommunicationProblem SolvingPublic Speaking

About the role

  • It also defines data security and adheres to compliance rigors across data needs for all business units.
  • 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.

Responsibilities

  • Lead the design, development and optimization of data warehouse solutions using AWS Redshift
  • Developing scalable and re-usable frameworks for ingestion of structured and semi-structured data
  • Ensures data warehouse features and capabilities are incorporated into data model designs to optimize performance, resiliency, and scalability.
  • Leading and coordinating the design and operationalization of Data Governance capabilities like - data lineage, data catalog, data quality, etc.
  • Implement intelligent testing frameworks that auto-generate test cases, predict bugs, and enable self-healing.
  • We're Here to Support You-Accommodations Upon Request
  • Our goal is to support every applicant in showcasing their talents and potential.

Requirements

  • Experience in implementing data governance programs
  • Strong understanding of
  • Excellent Communication, executive stakeholder management skills and the ability to navigate relationships across business units.
  • 3+ years of development experience with Python scripting experience.
  • Knowledge of data governance, security, and compliance standards (e.g., SOC 2, PCI DSS).
  • Demonstrated expertise in performance tuning in various DB environments with large volumes of data.
  • Familiarity with CI/CD pipelines (e.g., Jenkins, GitHub Actions) and infrastructure-as-code tools.
  • Experience with metadata management, data lineage tools, and data quality frameworks.
  • Familiarity with cloud platforms (AWS, Azure) and open-source governance.
  • All applicants must be legally authorized to work in the United States at the time of application and throughout the duration of employment, without the need for current or future sponsorship.

Nice to have

  • Financial technology domain knowledge
  • Microsoft Azure Data Engineer or other cloud certifications
  • Ability to work in the U.S. without sponsorship**
  • Green Dot is committed to providing an inclusive and accessible hiring experience for all candidates.
  • We will work with you to meet your needs in a way that respects your privacy and ensures equal opportunity.
  • Bachelor's and/or master's degree in computer science, Computer Engineering or related field preferred.
  • 10+ years of experience in enterprise Datawarehouse, data engineering or analytics platforms
  • 5+ years in leadership or management roles overseeing enterprise data teams

Skills

  • Maintain documents related to data mapping and logic

Compensation

  • The targeted full-time base salary for this position is $179,700 to $259,900 per year.
  • The final compensation will be determined by a number of factors such as qualifications, expertise, and the candidate's geographical location.

Equal opportunity

  • If you require a reasonable accommodation during any part of the application or interview process, we encourage you to let us know.

Visa & Work Authorization

  • However, we are currently unable to offer visa sponsorship.
  • All applicants must be legally authorized to work in the United States at the time of application and throughout the duration of employment, without the need for current or future sponsorship.
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This listing is sourced directly from Green Dot Corporation's careers page and normalized into a canonical job model.