
Location: Charlotte, NC (Hybrid)
Duration: Contract April 2026 to April 2028
We are seeking an experienced Big Data Developer to support enterprise risk technology initiatives. This role will focus on developing and maintaining large-scale data processing solutions using Spark, Scala, and Python within a distributed big data environment.
The ideal candidate will have strong experience working with big data frameworks, scheduling tools, and source control platforms, and will collaborate closely with engineering teams to support complex data processing and analytics initiatives.
Design and develop scalable big data solutions using Spark, Scala, and Python.
Build and optimize data pipelines and distributed data processing workflows.
Work with large datasets to support enterprise analytics and risk technology platforms.
Develop and maintain ETL and data transformation processes.
Optimize performance for large-scale Spark-based workloads.
Ensure reliability and scalability across distributed computing environments.
Implement job scheduling and automation using Autosys or similar scheduling tools.
Monitor and maintain data processing workflows to ensure operational stability.
Work closely with engineering teams, data engineers, and technical stakeholders to deliver scalable solutions.
Participate in design discussions and contribute to architecture decisions for data platforms.
Maintain source control and code versioning using Git.
Follow established development standards and collaborate through Agile processes.
5+ years of software engineering or big data development experience
Strong experience with:
Apache Spark
Scala
Python
Experience working with large-scale data processing systems
Experience with Autosys or similar job scheduling tools
Experience using Git or other version control platforms
Experience working in financial services or enterprise data environments
Experience building big data pipelines or ETL frameworks
Familiarity with distributed computing and data platform architecture
Apache Spark
Scala
Python
Big Data Development
ETL / Data Pipelines
Autosys Scheduling
Git Version Control
Distributed Data Processing