Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. About the Role We are seeking a highly skilled GCP Python Data Engineer to design, build, and optimize scalable cloud-based data solutions on Google Cloud Platform (GCP). The ideal candidate will possess strong Python development skills, hands-on experience with modern data engineering technologies, and expertise in building both batch and real-time data pipelines supporting analytics, AI/ML, and enterprise reporting initiatives. Work Authorization: Candidates must be authorized to work in the United States without current or future sponsorship. No visa sponsorship, transfers, or C2C arrangements are available. Key Responsibilities Data Engineering & Pipeline Development • Design, develop, and optimize ETL/ELT pipelines for structured and unstructured data. • Build scalable batch and streaming data processing solutions using GCP technologies. • Develop event-driven data processing solutions leveraging Pub/Sub and Cloud Functions. • Create and maintain data ingestion frameworks for enterprise data platforms. Data Storage & Analytics • Design and optimize data lake, lakehouse, and data warehouse solutions. • Build efficient data models supporting analytics, reporting, and AI/ML workloads. • Optimize performance, scalability, and cost efficiency of data pipelines and queries. Development & Automation • Develop robust Python-based solutions and frameworks. • Automate orchestration and workflow management using Cloud Composer (Airflow). • Implement CI/CD pipelines and deployment automation. • Apply software engineering best practices for testing, monitoring, and observability. Collaboration & Support • Partner with business stakeholders, analytics teams, data scientists, and engineers to deliver data solutions. • Troubleshoot production issues and perform root cause analysis. • Continuously improve reliability, scalability, security, and operational excellence. Required Qualifications • 5+ years of data engineering, software engineering, or related experience. • 2+ years of hands-on Google Cloud Platform (GCP) experience. • 2+ years of professional Python development experience. • Experience developing batch and real-time data pipelines. • Advanced SQL development and query optimization skills. • Experience with data warehousing, ETL/ELT, and modern data architecture patterns. • Strong understanding of cloud-native data engineering practices. Required Technical Skills Google Cloud Platform • BigQuery • Dataflow • Dataproc • Pub/Sub • Cloud Functions • Cloud Composer (Airflow) • Cloud Storage • Cloud SQL • IAM • Cloud Monitoring • Cloud Logging Programming & Data Engineering • Python • SQL • Bash/Shell Scripting • ETL/ELT • Data Warehousing • Data Lake / Lakehouse Architectures • Batch Processing • Real-Time Streaming Architectures Preferred Qualifications • Experience with Vertex AI and Google AI services. • Experience building AI/ML data platforms and pipelines. • Knowledge of Large Language Models (LLMs) and GenAI concepts. • Experience with Gemini models, Agentic AI frameworks, Prompt Engineering, RAG architectures, and Vector Search. • Experience with Dataproc, Spark, or PySpark. • Familiarity with event-driven architectures. • Experience with Terraform or Infrastructure as Code. • Understanding of cloud cost optimization and FinOps practices. • Financial Services industry experience. • Google Cloud Professional Data Engineer Certification. Keywords GCP, Google Cloud Platform, Python, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions, Cloud Composer, Airflow, SQL, ETL, ELT, Data Engineering, Data Pipelines, Streaming, Batch Processing, Cloud Storage, Cloud SQL, Vertex AI, Gemini, Generative AI, Agentic AI, LLM, RAG, Vector Search, Semantic Search, Spark, PySpark, Terraform, Data Warehouse, Data Lake, Lakehouse, CI/CD, Financial Services The base compensation range for this role in the posted location is: $115,000 - $145,000/ yearly. Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) • Life and disability insurance • Employee assistance programs • Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. 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 accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. capgemini.com Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

Requirements

Must-haves

Work Authorization: Candidates must be authorized to work in the United States without current or future sponsorship. No visa sponsorship, transfers, or C2C arrangements are available.
Data Engineering & Pipeline Development
Design, develop, and optimize ETL/ELT pipelines for structured and unstructured data.
Build scalable batch and streaming data processing solutions using GCP technologies.
Develop event-driven data processing solutions leveraging Pub/Sub and Cloud Functions.
Create and maintain data ingestion frameworks for enterprise data platforms.
Data Storage & Analytics
Design and optimize data lake, lakehouse, and data warehouse solutions.
Build efficient data models supporting analytics, reporting, and AI/ML workloads.
Optimize performance, scalability, and cost efficiency of data pipelines and queries.
Development & Automation
Develop robust Python-based solutions and frameworks.

Nice-to-haves

Experience with Vertex AI and Google AI services.
Experience building AI/ML data platforms and pipelines.
Knowledge of Large Language Models (LLMs) and GenAI concepts.
Experience with Gemini models, Agentic AI frameworks, Prompt Engineering, RAG architectures, and Vector Search.
Experience with Dataproc, Spark, or PySpark.
Familiarity with event-driven architectures.
Experience with Terraform or Infrastructure as Code.
Understanding of cloud cost optimization and FinOps practices.
Financial Services industry experience.
Google Cloud Professional Data Engineer Certification.
The base compensation range for this role in the posted location is: $115,000 - $145,000/ yearly.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gcppythonaimlci/cdsqlllmaccessibility

Platform: successfactors
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off