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Remote only
The Data Acquisition Team is the entry point to WEX’s Data-as-a-Service (DaaS) platform—responsible for ingesting, validating, and orchestrating raw data from dozens of internal systems and third-party providers.
As a Software Engineer 2 - Data Acquisition (Data Engineer), you’ll play a key role in designing and building robust, scalable, and extensible pipelines that feed the entire data ecosystem at WEX. You’ll work across multiple data domains and ingestion patterns—batch, streaming, and event-driven—while ensuring quality, performance, and governance are embedded in every step.
WEX is undergoing a data platform transformation—and this team builds the foundation. Every pipeline you create contributes directly to powering analytics, automation, and product intelligence across all business domains.
If you’re passionate about scaling data platforms from the ground up, this is your chance to help shape how WEX ingests and leverages its most valuable asset: data.
How you'll make an impact
Design and implement moderately complex ingestion pipelines that integrate with internal and external systems.
Develop reusable components for data transformation, validation, and logging.
Contribute to both batch and streaming ingestion flows, ensuring scalability and maintainability.
Support platform observability by enhancing monitoring, alerting, and error-handling features.
Participate in design discussions, code reviews, and incident investigations.
Partner with data consumers to understand requirements and translate them into ingestion solutions.
Improve automation and testing coverage to reduce manual effort and increase pipeline reliability.
Experience you'll bring
Solid programming skills in Python, Java, or Scala, with ability to write maintainable, production-ready code.
Good experience as software and data engineer, ideally working with data pipelines or distributed systems.
B.Sc. in Computer Science, Engineering, or related technical field (M.Sc. preferred). Equivalent experience considered.
Hands-on experience with ETL/ELT pipelines, schema management, and data modeling concepts.
Familiarity with streaming (e.g., Kafka, Kinesis, Spark Streaming) or batch frameworks.
Understanding of CI/CD, version control, and testing practices.
Exposure to observability practices such as logging, metrics, and tracing.
Strong sense of accountability and eagerness to take ownership of assigned deliverables.
