Data & ML Engineer

Calling all innovators - find your future at Fiserv.

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants, and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved.

If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

Data & ML Engineer

As a Data & ML Engineer, you will help build and support the data engineering, ETL, and MLOps capabilities that power Merchant Opportunity Analysis (MOA) and Offer Engine within the Digital Onboarding team. Merchant Opportunity Analysis (MOA) refers to the analytical capability used to identify merchant needs, growth opportunities, product fit, and offer recommendations that can improve onboarding, personalization, and customer acquisition outcomes within Digital Onboarding.

This role will focus on developing data pipelines, supporting feature preparation, maintaining ETL workflows, and helping operationalize machine learning outputs used for customer insights, personalization, and offer optimization. You will work closely with senior engineers, data scientists, backend engineers, and product partners to deliver reliable data and ML capabilities that support Digital Onboarding experiences.

• Build and maintain data pipelines that support MOA, Offer Engine, customer insights, personalization, and Digital Onboarding use cases.
• Develop ETL workflows using Python, SQL, AWS Glue, Qlik Data Integration, Snowflake, and related tools.
• Support ingestion, transformation, validation, and delivery of internal and external data sources.
• Assist with feature preparation, scoring workflows, model output processing, and ML integration patterns.
• Support MLOps activities including deployment workflows, monitoring, model output validation, and operational support.
• Implement data quality checks, error handling, reconciliation logic, and pipeline monitoring.
• Work with data scientists to understand feature needs and help prepare datasets for modeling and production use.
• Collaborate with backend engineers to support integration of model outputs, recommendation data, and customer insights into Digital Onboarding applications.
• Troubleshoot data pipeline issues, production defects, and integration failures.
• Follow engineering standards for code quality, CI/CD, documentation, security, and operational readiness.

• 4+ years of experience in data engineering, ETL development, ML engineering, analytics engineering, or software engineering.
• Hands-on experience with Python, SQL, and data pipeline development.
• Experience working with data integration or ETL tools such as AWS Glue, Qlik Data Integration, Snowflake, or similar platforms.
• Familiarity with AWS services such as S3, Glue, Lambda, Sage Maker, Cloud Watch, or related cloud services.