Lead Data Engineer

Capgemini; Vancouver; On-site; CAD 85,000 - 134,000; Full time

Job summary

Capgemini in Vancouver seeks a Lead Data Engineer with deep Microsoft Fabric expertise to design, build, and scale enterprise data platforms supporting large-scale analytics and business initiatives.

You will provide technical leadership across architecture, data engineering, governance, and delivery while mentoring teams and establishing best practices across the data ecosystem. The role combines hands-on engineering with solution architecture and cloud-based platform building.

Qualifications

• 10+ years of data engineering experience in enterprise environments.
• 3+ years of hands-on Microsoft Fabric experience.
• Strong SQL and PySpark development skills.
• Experience designing enterprise-scale data architectures and platforms.
• Proven ability to mentor and lead engineering teams.
• Experience leading architecture discussions, reviews, and governance.

Responsibilities

• Design and build enterprise-scale data solutions using Microsoft Fabric components.
• Lead architecture discussions, design reviews, and governance activities.
• Develop scalable ELT patterns and ingestion/transformation frameworks.
• Build and optimize high-volume batch and near real-time data pipelines.
• Establish data governance, quality, lineage, and metadata management.
• Drive performance, scalability, and cost-efficiency improvements.
• Mentor engineers and provide technical leadership across teams.
• Collaborate with stakeholders to deliver enterprise data solutions.
• Support Agile delivery, planning, estimation, and execution.

Skills

Data Engineering

Microsoft Fabric

SQL

PySpark

Data Governance

Leadership

Architectures

Stakeholder Management

Mentoring

Tools

Data Factory

Lakehouse

Warehouse

Spark Notebooks

OneLake

Power BI

Azure Databricks

Purview

Job description

Role Summary

We are seeking a Lead Data Engineer with deep Microsoft Fabric expertise to design, build, and scale enterprise data platforms supporting large-scale analytics and business initiatives. This role will provide technical leadership across architecture, data engineering, governance, and delivery while mentoring engineering teams and establishing best practices across the data ecosystem. The ideal candidate combines hands-on engineering expertise with strong solution architecture experience and a passion for building modern cloud-based data platforms.

Key Responsibilities

Design and implement enterprise-scale data solutions using Microsoft Fabric components including Data Factory, Lakehouse, Warehouse, Spark Notebooks, and OneLake.

Lead architecture discussions, technical design reviews, and engineering governance activities.

Develop scalable ELT frameworks and reusable ingestion and transformation patterns.

Build and optimize high-volume batch and near real-time data pipelines.

Establish data engineering standards, best practices, and governance frameworks.

Design and implement data quality, lineage, metadata management, and monitoring solutions.

Drive performance optimization, scalability, and cost-efficiency initiatives across the platform.

Mentor engineers through technical leadership, code reviews, and solution guidance.

Collaborate with business and technology stakeholders to deliver enterprise data solutions.

Support Agile delivery, sprint planning, estimation, and execution activities.

Required Qualifications

10+ years of Data Engineering experience.

3+ years of hands-on Microsoft Fabric experience.

Strong expertise with Data Factory, Lakehouse, Warehouse, Spark Notebooks, and OneLake.

Experience designing and implementing enterprise-scale data architectures and data platforms.

Proven experience building scalable ELT pipelines supporting large-volume batch and near real-time workloads.

Strong SQL and PySpark development skills.

Experience implementing data governance, lineage, metadata management, and data quality solutions.

Experience leading technical design discussions, architecture reviews, and engineering best practices.

Proven ability to mentor and lead engineering teams.

Strong communication and stakeholder management skills.

Preferred Qualifications

Experience building Customer 360 or large-scale customer data platforms.

Azure ecosystem experience including ADLS, Synapse, Databricks, or Purview.

Experience implementing enterprise data governance frameworks.

Power BI experience.

Previous experience leading distributed engineering teams.

The pay range that the employer in good faith reasonably expects to pay for this position is $61.79/hour - $96.54/hour. Our offered benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.