About the Company:
Ouro is a global, vertically-integrated financial services and technology company dedicated to the delivery of innovative financial empowerment solutions to consumers worldwide. Ouro’s financial products and services span prepaid, debit, cross-border payments, and loyalty solutions for consumers and enterprise partners.
Ouro's flagship product Netspend provides prepaid and debit account solutions that connect customers with secure, convenient access to global payment networks so they can manage their money and make everyday purchases. With a nationwide U.S. retail network, customers can purchase and reload Netspend products at 130,000 reload points and over 100,000 distributing locations.
Since Ouro's founding in 1999 by industry pioneers, Ouro products have processed billions of dollars in transaction volume and served millions of customers worldwide. The company is headquartered in Austin, Texas with employees worldwide.
Role Overview
We are seeking a seasoned Engineer to design, build, and optimize our data ecosystem. You will be responsible for migrating and managing complex data pipelines transitioning from legacy Oracle environments to Snowflake, using Python as your primary engine for automation and transformation. The ideal candidate is a strategic thinker who ensures data integrity at scale while staying ahead of the curve with emerging AI/ML integration.
Key Responsibilities
Legacy Integration: Maintain and optimize existing Oracle databases while leading strategic data migration efforts to the cloud
Automation: Utilize Python to automate repetitive data tasks, build custom API integrations, and manage workflow orchestration.
Performance Tuning: Conduct advanced SQL optimization and performance tuning within
Snowflake and Oracle to ensure low-latency data availability. Collaboration: Work closely with Data Science and Analytics teams to provide clean, structured, and performant datasets for business intelligence
AI Readiness: (Nice to Have) Explore and implement AI-driven data processing, such as LLM-based data cleaning or predictive pipeline monitoring
Technical Requirements (Must-Have)
Python: Expert-level proficiency for data manipulation (Pandas, PySpark) and scripting
Snowflake: Proven experience with Snowflake architecture (Snowpipe, Tasks, Streams, and
Zero-copy cloning)
Oracle: Strong background in Oracle RDBMS, PL/SQL development, and performance tuning
SQL: Mastery of complex SQL queries and window functions
Data Modeling: Deep understanding of Star/Snowflake schemas
Preferred Skills (Nice-to-Have)
AI/ML Integration: Familiarity with integrating AI models into data workflows or using
Snowflake’s AI features (Cortex, Document AI)
Orchestration: Experience with Airflow, Dagster, or Prefect
CI/CD: Knowledge of Git and automated deployment pipelines for data (dbt experience is a plus)
Understanding of Pre-paid card domain or any Payment domain
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