Lead Data Warehouse Engineer

Green Dot•Los Angeles, CA

2d•Hybrid

About The Position

Green Dot is seeking an experienced senior data warehouse developer to help deliver a next-generation, cloud-hosted data platform. The role focuses on designing, building, and supporting large-scale data warehouse solutions and transformation pipelines, including enterprise and cloud data warehouses, reporting environments, data lakes, data marts, and metadata repositories. The successful candidate will contribute hands-on technical expertise across data modeling, ETL development, performance tuning, service delivery, incident tracking, and change management, and will develop proofs of concept as well as production implementations. This is a structured hybrid position with an expectation of three days per week in the office and flexibility to work remotely on the remaining days. The position is open only to candidates who currently reside in West Los Angeles, California. Green Dot is unable to offer visa sponsorship; applicants must be authorized to work in the United States without current or future sponsorship. The targeted full-time base salary is $139,900 to $199,300 per year; final compensation depends on qualifications, expertise, and geographical location.

Requirements

At least 8 years of overall software development experience, primarily with data warehouse and business intelligence applications.
At least 8 years of hands-on development experience with cloud-based data warehouse platforms, such as Azure or AWS Databricks, AWS Redshift, Snowflake, or similar.
At least 8 years of development experience with the Informatica IDMC platform, including data integration, data quality, and data governance.
At least 5 years of hands-on development experience with relational databases such as MS SQL Server, PostgreSQL, or Oracle.
Experience with complex stored procedures and functions using SQL, optimization of SSIS packages, and Redshift database queries.
At least 5 years of development experience with Python and Windows batch or Unix Shell scripting.
Strong knowledge and experience in OLAP data modeling and design.
Demonstrated expertise in performance tuning across database environments with large volumes of data.
Experience building and scaling distributed, highly available systems in Azure or AWS cloud environments.
Expertise in understanding complex business needs, analyzing them, and designing and developing solutions.
Strong communication and professional skills, including the ability to navigate relationships across business units.
Ability to work in the United States without current or future visa sponsorship.
Currently reside in West Los Angeles, California.

Nice To Haves

Bachelor’s and/or master’s degree in Computer Science, Computer Engineering, or a related field (preferred).
Financial technology domain knowledge.
Knowledge of NoSQL databases such as MongoDB, Cassandra, or Azure Cosmos DB.
Microsoft Azure Data Engineer certification or other cloud certifications.

Responsibilities

Architect and maintain operational data stores (ODS), enterprise data warehouses (EDW), and related data intelligence environments, including data lakes, data marts, and metadata repositories.
Design and implement performant data movement pipelines using multiple ETL tools, batch processing, and real-time event streams.
Develop reusable, scalable frameworks for ingesting structured and semi-structured data and implement large-scale settlement and reconciliation frameworks.
Gather business and information requirements from product owners across functional units.
Design data architecture and data flow diagrams, and collaborate with peers to translate requirements into logical and physical data models.
Conduct design reviews and communicate design artifacts with stakeholders.
Create source-to-target data mappings, including multi-step transformations.
Incorporate database features and capabilities into data models and ETL pipelines to optimize performance, resiliency, and scalability.
Deliver and present proofs of concept for key technology components to project stakeholders and internal technology leaders.
Lead and coordinate the design and operationalization of Master Data Management, Data Quality, and Data Governance initiatives, including end-to-end data lineage.
Support delivery of other project components associated with cloud data platforms.
Troubleshoot data warehouse and ODS application issues and production errors, including critical production issues requiring immediate attention.
Perform other duties as assigned, including work on major new project initiatives.