Contract Data Platform Engineer focusing on Spark and ETL at a data services company. Designing scalable systems and collaborating with data scientists and engineers.
Responsibilities
Design and develop scalable, distributed, and resilient software systems.
Build, test, and optimize Spark-based ETL pipelines in Scala or Python.
Collaborate with researchers and data scientists to deliver production-ready data and models.
Participate in architecture discussions, peer reviews, and deployment processes.
Define and monitor technical and operational metrics to ensure system health and performance.
Continuously identify areas for optimization and efficiency improvements across services.
Mentor junior engineers and contribute to engineering best practices.
Drive innovation by staying current with emerging tools and technologies.
Requirements
5+ years of software engineering experience
Strong programming skills in Scala, Python, or Java
Spark experience for building and optimizing ETL jobs
Experience with Databricks (DBX) – workflows, data development, and debugging
Solid understanding of microservices architecture and distributed systems
Experience with AWS, Docker, and Kubernetes
Familiarity with Spring Boot, Terraform, and infrastructure-as-code
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