CCS Global Tech is a rapidly growing Information Technology company with a diverse portfolio of technology products and services and a large network of industry partnerships. With over 22 years of being a successful business with a global talent pool and presence, CCS is a certified Microsoft Gold Partner and specializes in delivering expert Microsoft based solutions for technical and business needs. We have been recognized by Inc. 500 Magazine as one of the fastest growing small companies in the Unites States.
we are a Tier 1 vendor for the City and County of San Francisco for Cloud Services, Staffing Services and Training Services. For this multi-year opportunity with a diverse set of needs to address, we are currently focusing on establishing partnerships with individuals as well as companies who can help us enhance our overall service portfolio, cut lead times, and ultimately help us deliver successfully. We currently hold sizable Government accounts in the San Francisco bay area including City and County of San Francisco, San Mateo County, and Santa Clara County.
We take great pride in our global reach and local influence. Your experience alongside our highly skilled and talented internal team who guide you along the way, offers key insights into what helps you stand out in a competitive job market.
If you are a partner company, please submit resumes with contact information of your own W2 Consultants only. Submitted consultants are expected to have excellent communication skills.
Position Overview
We are seeking a highly skilled Tech Lead with strong hands-on expertise in Python, Databricks, and Angular(Good to have) to lead the design, development, and implementation of scalable data and application solutions. The ideal candidate will guide engineering teams, architect end-to-end systems, and collaborate across functions to deliver high-quality, enterprise-grade products.
Key Responsibilities
- Technical Leadership
- Lead a cross-functional engineering team across backend, frontend, and data engineering streams.
- Own the full SDLC: architecture, design, development, code reviews, DevOps pipeline oversight, and production deployment.
- Provide technical direction, mentor developers, enforce coding best practices, and promote engineering excellence.
- Work closely with product owners, architects, and stakeholders to define technical strategy and roadmap.
- Backend Engineering (Python)
- Design and build robust microservices, APIs, and data processing frameworks using Python.
- Develop scalable ETL/ELT workflows and backend logic aligned with enterprise data standards.
- Implement best practices in error handling, logging, performance tuning, and automated testing.
- Data Engineering (Databricks)
- Build large-scale data pipelines and transformations using Databricks (PySpark/Spark SQL).
- Optimize data workflows for cost, performance, and reliability.
- Collaborate with data architects to define data models, governance, and quality frameworks.
- Integrate Databricks with cloud services (Azure/AWS) for end-to-end data solutions.
- Cloud & DevOps
- Work with CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins, etc.) for automated builds and deployments.
- Ensure seamless deployment and monitoring of applications in cloud environments.
- Drive improvements in observability, reliability, and system health using monitoring tools.
- Collaboration & Stakeholder Management
- Partner with business teams to translate requirements into scalable technology solutions.
- Estimate, plan, and track project deliverables.
- Guide teams in Agile development practices (Scrum/Kanban).
Required Skills & Qualifications
Technical Skills
- Strong hands-on experience with Python (Flask/FastAPI/Django desirable).
- Advanced knowledge of Databricks, PySpark, Spark SQL.
- Experience building large-scale distributed systems.
- Strong understanding of cloud platforms (Azure preferred, AWS/Google Cloud Platform acceptable).
- Familiarity with SQL/NoSQL databases (PostgreSQL, MySQL, Cosmos, MongoDB, etc.).
- Experience with Git, CI/CD pipelines, Docker, and containerized deployments.
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