Senior Software Architect - Platform

Calling all innovators - find your future '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  Title Senior Software Architect
- Platform About your role:

Data Commerce Solutions (DCS) is a Fiserv business unit that turns the company's differentiated data into scalable data platforms and products across credit, marketing, verification, fraud, and data insights. The Senior Software Architect
- Platform is the hands-on technical owner of reusable platform capabilities that support multiple DCS product verticals, combining architecture with direct software engineering. The desired outcome is secure, scalable, supportable platform services, including the capability to migrate data science proofs of concept into versionable, enterprise-scale production code.

What you’ll do:

Own the architecture, design, coding, testing, and production implementation of shared data and software platform capabilities; this is a hands-on engineering role, not an advisory-only position.

Create an engineering framework and automation that converts data science proofs of concept (notebooks, Python code, features, models, and validation logic) into modular, testable, version-controlled, deployable software, including CI/CD, validation, promotion, observability, rollback, and lineage.

Re-engineer proof-of-concept workloads for enterprise scale, including distributed processing, low-latency serving, batch throughput, fault tolerance, and cost optimization.

Build reference implementations and production code using technologies such as Java, Python, Spark, Spring Boot, APIs, microservices, containers, Kubernetes, and cloud-native data services.

Architect reusable, secure platform services for data ingestion, feature engineering, model execution, workflow orchestration, metadata, policy enforcement, and monitoring, with built-in security and privacy controls.

Establish coding standards, reusable libraries, templates, test harnesses, and paved-road deployment patterns, and partner with data scientists, product, security, Dev Ops, and SRE teams to define production-readiness criteria.

Lead architecture decisions through working code, prototypes, design documentation, and performance tests; participate in production issue resolution; and evaluate emerging technologies to improve reliability, scalability, and engineering velocity.

Experience you’ll need to have:10+ years of progressive software and data engineering experience, including significant responsibility for architecture and hands-on delivery of distributed systems.

Advanced coding proficiency in Java, plus strong working knowledge of Python and data science development patterns.

Demonstrated experience converting notebooks, experimental pipelines, models, or analytical prototypes into versioned, tested, maintainable production software.

Deep experience with Spark, microservices, REST or event-driven APIs, SQL and No

SQL systems, containerization, Kubernetes, and cloud architecture, preferably Microsoft Azure.

Experience designing CI/CD and MLOps or Data Ops workflows, including artifact repositories, automated testing, model or feature versioning, observability, and controlled promotion across environments.

Strong understanding of distributed systems, performance engineering, data formats such as Iceberg, Delta Lake, Avro, and Parquet, and Lakehouse, batch, and streaming architectures, plus hands-on knowledge of Git, Maven or Gradle, automated testing, Agile, and Dev Ops practices.

Proven ability to mentor early-career engineers while maintaining high engineering standards, and to communicate complex architecture through concise documentation, diagrams, and code.

Bachelor's degree in computer science, engineering, or a related field, or an equivalent combination of education and relevant experience.

Experience that would be great to have:

Experience building internal developer platforms, model or feature platforms, code transformation frameworks, or self-service engineering capabilities.

Experience with domain-driven design, test-driven development, infrastructure as code, SRE practices, and high-volume transaction…