GCP Python Lead Data Engineer

Position Title : GCP Python Lead Data Engineer Location : Charlotte, NC/ New York City, NYC (Onsite/Hybrid) Experience : 8+ Years Employee Type : Full Time with Benefits Note :- In Person Interview Job Description We are seeking a highly skilled GCP Data Engineer with strong Python expertise to design, build, and optimize scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have hands‑on experience developing batch and real‑time data pipelines, working with large‑scale datasets, and enabling analytics and AI/ML use cases. Key Responsibilities Design, build, and maintain scalable batch and real‑time data pipelines using GCP services such as Dataflow, Dataproc, and Pub/Sub Develop and optimize ETL/ELT workflows for structured and unstructured data processing Implement event‑driven data processing using Cloud Functions and Pub/Sub Build and manage data ingestion frameworks for streaming and batch data sources Data Storage & Processing Design and optimize data lakes and data warehouses using BigQuery and Cloud Storage Develop efficient data models to support analytics, reporting, and machine learning workloads Optimize performance and cost of data pipelines and queries Development & Automation Develop reusable and scalable solutions using Python Automate workflows and orchestration using Cloud Composer (Airflow) Implement CI/CD pipelines and deployment automation Collaborate with analytics, AI/ML, and business teams for data consumption needs Troubleshoot data issues and perform root cause analysis Continuously improve pipeline reliability, scalability, and performance Required Technical Skills Data Processing: Batch & Streaming architectures Concepts: Data Warehousing, ETL/ELT, Data Lake / Lakehouse architectures Required Experience 8+ years of overall data engineering or software engineering experience 3+ years of hands‑on Google Cloud Platform experience 3+ years of Python development 3+ years of experience building data pipelines (batch and streaming) Preferred Qualifications Experience with Dataproc (Spark/PySpark) for large‑scale processing Familiarity with event‑driven architectures Knowledge of Terraform or Infrastructure as Code Understanding of cost optimization (FinOps) Life At Capgemini Healthcare including dental, vision, mental health, and well‑being programs Financial well‑being programs such as 401(k) and Employee Share Ownership Plan Paid time off and paid holidays Paid parental leave Family building benefits like adoption assistance, surrogacy, and cryopreservation Social well‑being benefits like subsidized back‑up child/elder care and tutoring Mentoring, coaching and learning programs Employee Resource Groups Disaster Relief Disclaimer Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship. Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Click the following link for more information on your rights as an Applicant #J-18808-Ljbffr