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 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.

Lead Data Engineering Lead

Key Responsibilities

• 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.

Programming & Data Engineering

Advanced hands-on expertise in: Python PySpark SQL

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 BigQuery

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.

Required Experience

• 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 DevOps 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.

Job Description

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 of their data assets.

Job Description - Grade Specific

The role involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.

Compensation

The base compensation range for this role in the posted location is $125,000 to $150,000 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