Lead Data Engineer - GCP Data Architect
CapgeminiAbout the role
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.
Location:
This is a hybrid role based in Chicago, IL.
About the job you're considering
We are seeking a hands-on GCP Data Architect to design and build scalable, cloud-native data solutions on Google Cloud Platform. This role requires strong expertise in BigQuery, Dataflow, Pub/Sub, and Python, along with a solid understanding of distributed systems, batch and streaming data architectures, and modern data engineering practices. The ideal candidate is both an architect and a doer, capable of guiding technical direction while actively contributing to implementation and delivery.
Your role
- Design and architect scalable, secure, and cost-effective data platforms on Google Cloud Platform.
- Lead the development of batch and real-time data ingestion and processing solutions.
- Design modern data architectures leveraging BigQuery, Dataflow, Pub/Sub, and related GCP services.
- Evaluate and implement appropriate distributed processing and data movement patterns for varying business requirements.
- Develop and optimize enterprise-scale ETL/ELT pipelines.
- Collaborate with data engineers, application developers, platform teams, and business stakeholders.
- Provide architectural guidance for data modeling, storage, governance, performance, and scalability.
- Support cloud-native application deployment patterns using Cloud Run and/or GKE.
- Contribute to infrastructure automation, DevOps, and CI/CD best practices.
- Participate in architecture reviews, technical design sessions, and code reviews.
- Troubleshoot and optimize data processing workloads and platform performance.
Skills & experience
- 7+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platform development.
- Strong hands-on experience with:
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- BigQuery
- Dataflow
- Pub/Sub
- Python
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- Experience designing and implementing data solutions on Google Cloud Platform (GCP).
- Strong understanding of:
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- Distributed systems
- Data pipeline architecture
- Batch and streaming processing patterns
- Large-scale data processing and analytics
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- Experience developing and supporting production-grade data pipelines.
- Ability to balance architectural strategy with hands-on implementation.
- Strong communication and stakeholder management skills.
The base compensation range for this role in the posted location is: $144,890 - $190,117.
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-
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