Data Engineer Lead

We are seeking a Data Engineer with strong expertise in Google Cloud Platform (GCP) and PySpark to design, build, and optimize scalable data pipelines. The role focuses on processing large-scale datasets, enabling analytics, and supporting data-driven decision-making within a cloud-native ecosystem. The ideal candidate will have hands-on experience with distributed data processing, cloud data services, and ETL/ELT frameworks, with a strong engineering mindset toward performance, scalability, and reliability.

Core Responsibilities

1. Data Pipeline Development Design and develop scalable data pipelines using PySpark Process and transform large datasets (batch and streaming) Build reusable data processing frameworks

2. GCP Data Engineering Work extensively with GCP services, including: BigQuery (data warehousing) Cloud Storage (data lake) Dataflow / Dataproc (processing) Optimize ingestion, storage, and retrieval of datasets in GCP

3. ETL / ELT Engineering Develop and maintain end-to-end ETL/ELT pipelines Ensure: Data quality Data consistency Schema evolution handling

4. Performance & Optimization Optimize PySpark jobs for: Large-scale distributed processing Memory and execution efficiency Tune query performance in BigQuery

5. Data Integration & Collaboration Collaborate with: Data scientists Analysts Application teams Enable datasets for analytics, reporting, and ML workflows

6. DevOps & Automation Implement CI/CD for data pipelines Use Git for version control Automate deployments and monitoring of data workflows Required Technical Skills Programming & Processing Strong Python + PySpark Experience with Spark (RDD/DataFrame APIs) Cloud Platform Hands-on Google Cloud Platform (GCP): BigQuery Cloud Storage Dataproc / Dataflow Pub/Sub (preferred) Data Engineering ETL/ELT pipeline development Data modeling (structured & semi-structured data) SQL (advanced) Tools & Frameworks Airflow / Composer (workflow orchestration) CI/CD pipelines Nice-to-Have Skills Streaming frameworks (Kafka / Pub-Sub streaming) Delta Lake / Iceberg / Lakehouse patterns Machine Learning pipeline exposure Data governance and lineage tools

Strong data engineering mindset (not just scripting) Experience with large-scale datasets (TB-level) Comfortable working in cloud-native, distributed environments Proactive in debugging and optimizing data pipelines’

The base compensation range for this role in the posted location is: 62,000 - 72,000

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.

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., 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.