- Location
- Australia - Melbourne Office
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Closing date
- Today
- Source
- Workday
Description
About the Role
The Data Acquisition Team is the entry point to WEX’s Data-as-a-Service platform, responsible for ingesting, validating, mastering, and delivering trusted data from internal systems and third-party providers.
We are seeking a Staff Software Engineer who can architect and evolve core data platform capabilities, with an initial focus on enterprise Master Data Management. You will design production software, APIs, data services, and integration frameworks that establish trusted business identities, relationships, hierarchies, reference data, and golden records across WEX.
This role is ideal for an engineer who combines strong software and systems engineering skills with hands-on development, architectural leadership, and mentorship. Experience building enterprise MDM solutions is preferred, but the role is not dependent on a particular MDM product.
Practical AI development experience is required. You will use AI-assisted engineering throughout the development lifecycle and help build AI-enabled capabilities that improve data quality, engineering productivity, platform operations, and business data experiences.
WEX is undergoing a data platform and AI transformation. This team builds the foundation by ensuring that data entering the platform is reliable, governed, correctly identified, and reusable across analytics, automation, operational applications, and AI products.
What You’ll Do
Architect and develop scalable software, APIs, and batch or streaming data pipelines.
Lead the design and implementation of enterprise MDM capabilities, including identity resolution, golden records, matching, survivorship, relationships, hierarchies, and reference data.
Build reusable platform components for validation, data contracts, orchestration, retries, audit logging, lineage, and reconciliation.
Apply AI-assisted development across solution design, coding, testing, debugging, and documentation, and build AI-enabled capabilities where they provide value.
Improve platform performance, reliability, observability, security, and cost efficiency.
Establish automated testing and CI/CD practices for software, data models, integration logic, and platform configuration.
Lead production troubleshooting, root-cause analysis, and preventive improvements.
Mentor engineers and partner with Product, Architecture, Data, Risk, and Governance teams to shape technical direction.
What You Bring
8+ years of software engineering experience, including distributed systems, cloud platforms, or large-scale data solutions.
Strong software engineering fundamentals and advanced development experience with Python, Java, or another modern programming language.
Experience building production APIs, cloud services, data pipelines, and batch or event-driven integrations.
Hands-on experience using AI-assisted development tools and building AI-enabled solutions using model APIs, retrieval patterns, agents, or similar technologies.
Understanding of AI risks, including accuracy, security, privacy, model limitations, and the need to validate AI-generated outputs.
Strong knowledge of automated testing, CI/CD, observability, data contracts, schema evolution, lineage, and data quality.
Ability to lead architecture decisions, troubleshoot complex production problems, mentor engineers, and influence technical direction.
Experience building enterprise MDM solutions is preferred, including knowledge of identity resolution, matching, survivorship, golden records, and commercial platforms such as Reltio.
Preferred Experience
Experience designing, building, or operating enterprise MDM systems.
Knowledge of identity resolution, golden records, matching and merging, survivorship, crosswalks, hierarchies, relationships, reference data, data stewardship, and data quality.
Hands-on experience with Reltio or another enterprise MDM platform.
Experience delivering Customer 360, customer onboarding, Search Before Create, or enterprise identity services.
Experience with technologies such as Snowflake, dbt, Kafka, AWS, S3, infrastructure as code, and cloud observability platforms.
Experience modernizing or migrating legacy data or MDM solutions.
Experience in financial services, payments, risk, or another regulated environment.
