Job
Description
At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities,"collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow."Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.
Your role
As a Senior Azure Data Engineer, you will be responsible for architecting, developing, and optimizing enterprise-grade data solutions on Microsoft Azure. You will lead the design and implementation of scalable data platforms, data lakes, and analytics systems, ensuring alignment with business goals and cloud strategy. This role demands deep technical expertise in Azure/AWS services, data modelling, and pipeline orchestration, along with the ability to mentor junior engineers and collaborate across teams. A foundational understanding of Generative AI (GenAI) is desirable, particularly in integrating AI-driven data enrichment and automation into Azure-based workflows. Architect and implement end-to-end data solutions using ADF, Synapse Analytics, Databricks, AWS Glue, AWS Data Pipeline, Amazon EMR.Design and manage data lakes, data warehouses, and streaming data architectures. Lead cloud migration and modernization initiatives for legacy data systems.
Ensure data governance, security, and compliance across all Azure data assets.Collaborate with enterprise architects, data scientists, and business stakeholders to deliver scalable analytics solutions.Implement CI/CD pipelines, DevOps practices, and Infrastructure as Code (IaC) using tools like Terraform or ARM templates
Your profile
Bachelors/masters degree in computer science, Engineering, or related field. 9"“12 years of experience in data engineering or architecture roles, with at least 4+ years on Azure/AWS Evaluate and integrate GenAI capabilities (e.g., Azure OpenAI, Copilot Studio, Amazon SageMaker, Bedrock, Kendra) into data engineering workflows. Guide architectural decisions and mentor junior engineers on best practices. Proven experience in - Cloud migration and solution architecture for large-scale data systems. Azure Data Factory, Azure Synapse, Azure Databricks, Azure SQL, Cosmos DB, Blob Storage, Data Lake Storage Gen2, AWS Glue, Redshift, EMR, DynamoDB, RDS, S3 etc. ETL/ELT pipelines, data modelling, and MPP databases (e.g., Snowflake, Redshift, Teradata). BI Reporting (preferably on Power BI). Strong programming skills in Python, SQL, and Spark. Familiarity with GenAI tools like Azure OpenAI, AWS AI Services, Hugging Face, or LangChain is a plus. Knowledge of streaming data platforms such as Kafka, Azure Event Hubs, Azure Stream Analytics, Amazon Kinesis. Excellent communication, leadership, and stakeholder management skills.
What you will love about working here
We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance.
At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities.
Equip yourself with valuable certifications in the latest technologies such as Generative AI.
