Job TitleSenior Data & ML Engineer
About Your role:As a Senior Data & ML Engineer, you will play a lead technical role in building and operationalizing the data engineering, ETL, and MLOps capabilities that support 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 designing scalable data pipelines, production-ready feature workflows, model integration patterns, and reliable data services that enable customer insights, personalization, and offer optimization. You will work closely with data scientists, backend engineers, product teams, and platform partners to ensure data and machine learning capabilities are reliable, observable, secure, and ready for enterprise-scale use.
What You'll Do:- Lead the design and implementation of data pipelines supporting MOA, Offer Engine, customer insights, personalization, and Digital Onboarding use cases.
- Build scalable ETL and data integration workflows using Python, SQL, AWS Glue, Qlik Data Integration, Snowflake, and related technologies.
- Design and support feature pipelines, scoring workflows, model output processing, and ML integration patterns for production use cases.
- Partner with data scientists to productionize machine learning models, analytical features, segmentation outputs, and recommendation logic.
- Establish and mature MLOps practices including model packaging, deployment automation, monitoring, lineage, governance, and retraining support.
- Implement data quality checks, reconciliation processes, observability, exception handling, and operational controls across data pipelines.
- Build batch and near-real-time data movement patterns to support onboarding journeys, merchant matching, and offer recommendation workflows.
- Collaborate with backend engineers to integrate customer insights, recommendation outputs, and offer data into Digital Onboarding APIs and workflows.
- Provide technical leadership through design reviews, code reviews, solution documentation, and mentoring of other engineers.
- Partner with architecture, security, infrastructure, and governance teams to ensure solutions meet enterprise standards.
Experience You'll Need to Have:- 8+ years of experience in data engineering, ML engineering, ETL development, analytics engineering, or platform engineering.
- Strong hands-on experience with Python, SQL, data pipeline development, and production-grade data engineering patterns.
- Experience designing and building ETL pipelines using AWS Glue, Qlik Data Integration, Snowflake, or comparable technologies.
- Experience with AWS services such as S3, Glue, Lambda, SageMaker, CloudWatch, Step Functions, ECS/EKS, or similar cloud-native services.
- Experience supporting production ML workflows including feature engineering, batch scoring, model deployment, and model monitoring.
- Strong understanding of data modeling, data quality, partitioning, orchestration, metadata, observability, and lineage.
- Experience building reliable, secure, and scalable data services for customer-facing or business-critical platforms.
- Experience with CI/CD, DevSecOps, version control, automated testing, and release management practices.
- Strong troubleshooting skills across data pipelines, ML workflows, application integrations, and production issues.
- Ability to influence technical direction and collaborate across engineering, data science, product, and business teams.
- Bachelor's degree in Computer Science, Information Technology, Information Systems, or a related field (or equivalent industry experience).
Experience That Would Be Great to Have:- Experience supporting offer engines, recommendation systems, personalization, customer insights, Digital Onboarding, or customer acquisition platforms.
- Experience with MLOps platforms, model registries, feature stores, automated retraining, and ML monitoring frameworks.
- Experience with CDC, streaming, event-driven integration, or near-real-time data pipelines.
- Experience working with merchant, product, application, transaction, or behavioral datasets.
- Experience within financial services, fintech, payments, merchant onboarding, or digital acquisition platforms.
- Experience with Agentic SDLC, AI-assisted development, automated testing, and developer productivity tooling.
- AWS Data Analytics, Machine Learning, or Solution Architecture certifications.
Important information about this role:- This role is on-site Monday through Friday. Fiserv considers in-person collaboration to be an essential part of this role as in-person office experiences help you with your overall onboarding experience and leads to stronger productivity
- This is a full-time, direct-hire position, and no contract options for unsolicited agency submissions will be considered.
- All offers of employment are contingent on standard background checks. Fiserv and certain of its affiliated companies are federal, state, and/or local government contractors. Should this position support a Federal Government contract, now or in the future, the successful candidate will be subject to a background check conducted by the U.S. Government to determine eligibility and suitability for federal contract employment for public trust or sensitive positions. Positions that support state and/or local contracts also may require additional background checks to determine eligibility and suitability.
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This role is not eligible to be performed in Colorado, California, District of Columbia, Hawaii, Illinois, Massachusetts, Maryland, Minnesota, New Jersey, New York, Nevada, Rhode Island, Vermont, Virginia, Maine or Washington.
It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.
Please note that salary ranges provided for this role on external job boards are salary estimates made by outside parties and may not be accurate.
Thank you for considering employment with Fiserv. Please:
- Apply using your legal name
- Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).
