Senior Azure Data Engineer - Lead Data Pipelines (Contract)

Capgemini; Brampton; On-site; CAD 87,000 - 135,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Retirement benefits

Job summary

Capgemini is seeking a data engineering lead to design, build, and scale data pipelines using Azure Data Factory and Azure Databricks in Brampton, Canada. You will guide a 10–15 person team and collaborate with executives, product, and analytics stakeholders to deliver robust data solutions.

You will own data ingestion, transformation, and loading, ensure quality and security, and mentor the team on best practices in data engineering and DevOps.

Qualifications

• Proven leadership experience managing technical teams.
• Strong presentation, communication, and stakeholder management skills.
• Experience working in Agile and DevOps-driven environments is preferred.

Responsibilities

• Design, develop, and maintain scalable and efficient data pipeline architectures using Azure Data Factory (ADF).
• Build and manage ETL/ELT processes using Azure Databricks, with a strong understanding of Apache Spark and PySpark frameworks.
• Assemble and manage large, complex datasets that support both functional and non-functional business requirements.
• Develop and maintain data ingestion, transformation, and loading solutions using SQL and Azure Big Data technologies.
• Work closely with Executive, Product, Data, and Design teams to address data-related technical challenges and support data infrastructure needs.
• Create and maintain data tools that enable analytics and data science teams to build, optimize, and scale business solutions.
• Collaborate with data engineers, analysts, and data scientists to enhance the functionality and performance of data platforms and systems.
• Ensure data quality, reliability, security, and governance across the data ecosystem.
• Provide technical leadership and guidance to a team of 10–15 members.
• Drive project delivery, mentor team members, and support best practices in data engineering and development.
• Deliver effective presentations and communicate technical concepts clearly to both technical and business stakeholders.
• Demonstrate strong leadership, stakeholder management, and problem-solving capabilities.

Skills

Leadership

Data pipelines

Azure Data Factory

Azure Databricks

Apache Spark

PySpark

SQL

Data governance

Data quality

Security

Tools

Azure Data Factory

Azure Databricks

Apache Spark

PySpark

SQL

Job description

Capgemini is seeking a data engineering lead to design, build, and scale data pipelines using Azure Data Factory and Azure Databricks in Brampton, Canada. You will guide a 10–15 person team and collaborate with executives, product, and analytics stakeholders to deliver robust data solutions.

You will own data ingestion, transformation, and loading, ensure quality and security, and mentor the team on best practices in data engineering and DevOps.