Senior Data Engineer

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 bya 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.

We are seeking a highly experienced Senior Data Engineering Lead with 8+ years of experience in modern data engineering, data warehousing, and data lake technologies across cloud platforms, including Microsoft Azure, Google Cloud Platform (GCP), and AWS. The ideal candidate will have strong technical expertise, proven leadership abilities, and experience designing scalable data solutions while collaborating with business and technical stakeholders.

Design, build, and implement scalable data pipelines using Microsoft Fabric, including Azure Data Factory, PySpark, Spark SQL, and Python. Develop and maintain ETL/ELT processes to ingest, transform, and load data from multiple sources into data warehouses, data lakes, and analytical platforms. Optimize large-scale data processing workflows to improve performance, scalability, and reliability. Implement and maintain data security, governance, and compliance standards in accordance with enterprise and regulatory requirements.

Collaborate with business stakeholders, architects, and engineering teams to gather requirements and deliver effective data solutions. Lead development efforts, provide technical guidance, and ensure delivery of high-quality solutions within project timelines. Required Technical Skills Programming & Data Engineering Advanced hands-on expertise in:
Python PySpark SQL Strong experience in data modeling, query optimization, and schema design. Cloud & Data Platforms Strong proficiency with Microsoft Azure Cloud Services. Experience with Microsoft Fabric and related technologies:
Azure Data Factory Azure Synapse Analytics Azure Data Lake Storage Databricks Working knowledge of AWS and/or Google Cloud Platform (GCP) data services is highly desirable. Data Warehousing & Data Management Minimum 8 years of experience in modern data engineering, data warehousing, and data lake technologies.

Extensive experience with enterprise data warehouse platforms, including one or more of:
Azure Synapse Analytics Azure SQL Database Snowflake Amazon Redshift Google Big Query Strong understanding of data warehouse best practices, development standards, and methodologies. Experience with:
Azure Data Lake Storage Azure Blob Storage Azure Cosmos DB Azure SQL Database ETL/ELT & Architecture Experience with ETL/ELT tools such as:
Azure Data Factory (ADF) Informatica Talend Practical experience implementing Medallion Architecture and modern data lakehouse patterns.

8+ years of experience in data engineering, data warehousing, and cloud-based data platforms. 12+ years of experience in SQL development, schema design, and dimensional data modeling. Experience developing and optimizing big data solutions using Spark-based technologies. Strong analytical, troubleshooting, and problem-solving capabilities. Demonstrated experience leading technical teams and mentoring engineers. Preferred Qualifications Experience with Databricks (highly preferred). Experience with Azure Dev Ops and CI/CD implementation.

Knowledge of cloud migration strategies and methodologies. 2+ years of experience with Power BI. 5+ years of experience with reporting and visualization tools such as Tableau, OBIEE, or similar platforms.

Leadership Expectations Lead and mentor data engineering teams. Drive technical design decisions and architectural standards. Manage stakeholder expectations and communicate effectively across technical and business teams. Ensure timely delivery of high-quality, scalable, and secure data solutions.

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value…