Lead ETL Engineer

Green Dot•Los Angeles, CA

12d•Remote

About The Position

We’re looking for talented professionals, anywhere in the United States, to join us in bringing smart money management and payment solutions to everyone’s fingertips. At Green Dot, we are evolving to a new and permanent “Work from Anywhere” model designed to maximize the benefits of remote work, promote and enable a strong culture of performance and connectedness, and attract the best and brightest talent who align with our entrepreneurial spirit and mission. <<>><<>><<>><<>><<>><<>><<>><<>><<>><<>> JOB DESCRIPTION Role Overview This is an exciting opportunity for an experienced Lead data warehouse developer of large-scale data solutions. You will join a team delivering a transformative next-gen cloud hosted data platform. The ideal candidate will have a proven track record in implementing next-gen cloud data solutions and transformation pipelines for large scale organizations. We are seeking someone with deep technical skills in a variety of data warehouse related technologies to play an important role in developing and delivering early proofs of concept and production implementation. The successful candidate will have hands-on experience in a multitude of data domains; including building data warehouse models, ETL development, automated testing framework, performance tuning, service delivery, incident resolution tracking, and change management.

Requirements

Bachelor’s and/or master’s degree in computer science, Computer Engineering or related field preferred.
8+ years of overall software development experience is required primarily with Data warehouse applications, with 3+ years in a technical leadership role.
3+ years of hands-on development experience in Cloud-based data warehouse platform (AWS Redshift preferred) and experience with ETL tools (Informatica Cloud preferred).
3+ years of development experience with Python scripting experience.
Strong knowledge and experience in OLAP data modeling & design.
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.
Expertise in understanding complex business needs, analyzing, designing, and developing solutions.
Communication and professional skills and the ability to navigate relationships across business units.

Nice To Haves

Experience in fintech or enterprise data warehouse platforms.
Familiarity with data warehouse operational domains such as partner reporting, compliance analytics, and business intelligence.
Contributions to open-source QA frameworks or technical publications.
Demonstrated leadership in building scalable QA practices, as outlined in internal QA leadership guidance.

Responsibilities

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.
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).