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Lead Cloud Engineer - Apache Spark / Google Cloud Platform / Python / Microservices

Technology
Strategic Staffing Solutions
Charlotte, United States3 weeks agoUntil 6/10/2026
Full timeHybrid

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 / Google Cloud Platform / Python / Microservices

Location: Charlotte, NC

Hybrid work- some on site work

Contract Length: 12 months

Job ref# 245704

Senior hands-on engineer supporting the Model Risk & Finance platform in a hybrid cloud environment (Google Cloud Platform 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

Core Technologies

  • Apache Spark / PySpark (required)
  • Google Cloud Platform (Google Cloud Platform) (strongly preferred)
  • Kubernetes / OpenShift
  • Python (Django, APIs)
  • CI/CD: GitHub Actions, Helm, Harness

Key Initiative

  • Migration from Hadoop to Google Cloud Platform
  • Build and support hybrid cloud platform (PyFarm)
  • Ongoing platform engineering and optimization after migration

Top Skill Priorities

  1. Spark at scale (production experience)
  2. Hands-on Google Cloud Platform experience (not just exposure)
  3. Kubernetes / OpenShift
  4. Python and microservices development
  5. Debugging and performance tuning of distributed systems

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 Google Cloud Platform experience

Keywords
OCamlApache HadoopApache SparkOpenShiftCloud computingDjangoPythonHadoopApache LicenseApache Http ServerCI / CDBig dataDebuggerGithubKubernetesDebuggingCI/CD

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