Sr Staff Software Engineer- Data Platform

WEXWEXUS•Remote, OH

1d•$220,000 - $255,800

About The Position

As a Sr. Staff Data Platform Engineer, you will be the primary architect and visionary for the core data infrastructure that powers the entire enterprise. This is a "platform-as-a-product" role; your mission is to build the internal foundation—creating the high-performance engines, abstraction layers, and self-service frameworks that enable hundreds of other engineers to move faster. You will operate at the intersection of Systems Programming and Data Engineering, solving "hard-tech" problems like automated schema evolution, multi-engine compute optimization, and global data discovery. As a top-level technical individual contributor, you will bridge the gap between long-term business strategy and deep-kernel technical execution, ensuring WEX’s data platform remains a competitive advantage. Is this role for you? YES, if: You are a Backend/Software Engineer who loves solving "Big Data" problems, building APIs for data discovery, and optimizing distributed systems. NO, if: Your primary expertise is writing SQL queries, building Tableau dashboards, or managing ETL workflows without deep experience in Java or Python system architecture.

Requirements

15+ years in software engineering and distributed systems, with at least 4 years in a principal or staff-level capacity leading platform-scale initiatives.
Strong fundamentals on software engineering, system architecture, and scalable production applications (Algorithms, Data Structures, and System Design).
Experience in the Java/J2EE ecosystem (Spring Boot, Microservices) and python. Writing clean, testable, and high-performance code.
Experience building platforms/framework engines and APIs that power data movement, rather than just building ETL/ELT pipelines.
Deep internal knowledge of Apache Iceberg, Hudi, or Delta Lake (metadata management, manifest files, and compaction strategies).
Experience contributing to or deeply customizing open-source data projects (e.g., Spark, dbt).
Extensive experience designing and building high-throughput, fault-tolerant data pipelines and orchestration frameworks.
Extensive experience with cloud architecture and services, including AWS (S3, EMR, Kubernetes, Lambda) and Azure.
Deep understanding of CI/CD automation, modern development tools, Git Actions, Terraform and frameworks.
Experience leveraging AI Code Gen platforms into software development lifecycle (SDLC) to automate code generation, reviews, generate unit tests, and perform root-cause analysis of system failures.
Ability to architect the infrastructure required to support AI Agent development by enabling vector database integration.
Proven track record of "leading by influence"—driving adoption of new technologies across multiple autonomous teams.
Ability to communicate complex architectural trade-offs to C-suite executives and junior engineers alike.
Bachelor’s or Master’s degree in Computer Science (Distributed Systems focus) preferred, or equivalent deep industry experience.

Responsibilities

Define the 3-5 year technical roadmap for the Data Lakehouse, deciding how storage, compute, and metadata layers interact.
Build internal SDKs, CLI tools, and automated orchestration frameworks to abstract cloud complexity.
Prototype and benchmark emerging technologies to keep the platform at the bleeding edge of performance and cost-efficiency.
Architect "compliance-by-design" systems, automating data lineage, PII masking, and fine-grained access control.
Facilitate real-time data ingestion by implementing streaming support for Open Telemetry data from AI Agents into the Data Lake, drive the development of advanced AI evaluation metrics and reporting.
Set the gold standard for code quality and system design, lead Cross-Functional Architecture Reviews, and serve as the final escalation point for complex system outages or performance bottlenecks.
Foster an "Engineering Community," influencing the hiring bar and professional development paths for the entire data engineering organization.