Software Engineer – Data Acquisition
Remote / Online - Candidates ideally in
Dallas, Dallas County, Texas, 75202, USA
Listed on 2026-10-23
Dallas, Dallas County, Texas, 75202, USA
Listing for:
WEX
Remote/Work from Home
position Listed on 2026-10-23
Job specializations:
-
Software Development
Software Engineer, DevOps, Backend Developer, Cloud Engineer - Software
Job Description & How to Apply Below
This is a remote position; however, the candidate must reside within 30 miles of one of the following locations:
Portland, ME;
Boston, MA;
Chicago, IL;
Dallas, TX;
San Francisco Bay Area, CA; and Seattle/WA.About the Role 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 Staff Software Engineer, you will own the technical direction and delivery of core data acquisition platform capabilities. You will remain hands-on while leading architecture decisions, developing reusable ingestion services, and guiding engineers across teams. Your work will support batch, change data capture (CDC), and event-driven ingestion, with clear expectations for data quality, reliability, security, and cost.
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.
What You’ll DoBuild and maintain high-performance data acquisition pipelines that integrate with a variety of systems across WEX and third-party vendors.
Lead the design and delivery of a modular ingestion platform with reusable connectors and configuration-driven onboarding. Establish metadata and configuration patterns that reduce source-specific development and support Data Acquisition as a Service.
Build schema validation, completeness checks, reconciliation, duplicate prevention, and audit logging into shared ingestion components.
Support safe retries, replay, backfills, and schema evolution so failures can be recovered without losing or incorrectly duplicating data.
Design batch, CDC, and streaming ingestion patterns that meet agreed freshness, throughput, and recovery requirements. Evaluate performance, source-system impact, and operating cost when selecting and extending ingestion technologies.
Ensure traceability, lineage, and security through integration with control plane and governance systems.
Lead design and code reviews, maintain technical specifications and architectural decisions, and mentor engineers in reusable platform design.
Establish automated testing and CI/CD practices for ingestion code, connector configuration, and infrastructure, with validation before production deployment.
Partner with the established production support process on complex escalations, root-cause analysis, and preventive engineering improvements.
What You Bring
Required:
B.Sc. in Computer Science, Engineering, or related technical field; M.Sc. a plus but not required.
8+ years of software engineering experience, including delivery of production distributed systems or data platforms and demonstrated technical leadership across team boundaries.
Strong programming skills in Python, Java, Scala, or another systems-focused language.
Experience with data integration and ingestion pipelines—you understand what it means to bring data in from source systems, transform it, and deliver it reliably downstream.
Solid grasp of engineering fundamentals, including version control, modular design, testing, and performance tuning.
Demonstrated experience designing and operating production integrations that handle schema evolution, failure recovery, observability, and secure access.
Ability to lead architecture decisions, explain engineering tradeoffs, resolve dependencies across teams, and guide implementation through production adoption.
Practical experience using AI-assisted engineering tools for…
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