Senior Cloud Engineer - Apache Spark, GCP, Python, Microservices
Lead Cloud Engineer for Model Risk & Finance platform in hybrid cloud environment. Building, supporting, and enhancing distributed data platforms and backend systems. Working on large-scale Spark/PySpark data processing and cloud migration.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
STRATEGIC STAFFING SOLUTIONS HAS AN OPENING!
This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position. Visa Sponsorship is Available! The details are below.
“Beware of scams. S3 never asks for money during its onboarding process.”
Job title: Lead Cloud Engineer – Apache Spark / GCP / Python / Microservices
Location: Charlotte, NC
Hybrid work- some on site work
Contract Length: 12+ months
Pay: 85 an hr on W2
Senior hands-on engineer supporting the Model Risk & Finance platform in a hybrid cloud environment (GCP + OpenShift/Kubernetes).
This is a backend-focused role centered on distributed data processing and platform engineering — not UI development.
Key Responsibilities
- Build, support, and enhance distributed data platforms and backend systems
- Develop APIs, workflows, and platform components using Python
- Work on large-scale Spark/PySpark data processing systems
- Support and optimize Kubernetes/OpenShift-based environments
- Contribute to CI/CD pipelines and platform automation
- Debug, troubleshoot, and optimize distributed systems at scale
- Support ongoing platform enhancements post cloud migration
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Core Technologies
- Apache Spark / PySpark (required)
- Google Cloud Platform (GCP) (strongly preferred)
- Kubernetes / OpenShift
- Python (Django, APIs)
- CI/CD: GitHub Actions, Helm, Harness
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Key Initiative
- Migration from Hadoop to GCP
- Build and support hybrid cloud platform (PyFarm)
- Ongoing platform engineering and optimization after migration
Top Skill Priorities
- Spark at scale (production experience)
- Hands-on GCP experience (not just exposure)
- Kubernetes / OpenShift
- Python and microservices development
- Debugging and performance tuning of distributed systems
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Nice to Have
- AI/LLM integration experience (building capabilities)
- GPU or platform-level AI exposure
- Hadoop migration experience
Team Environment
- Platform and Application Development team
- Works closely with Data and Support teams
- US and India team presence
Target Candidate Profile
- Platform Engineer (Data / ML platform)
- Cloud Data Engineer (Spark-heavy)
- Big Data Engineer with Kubernetes and GCP experience
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