Databricks Data Architect

LED FastStart

6d•Remote

About The Position

We're growing rapidly and are looking for a senior-level data architect to help us design and build a large-scale cloud-based data lake. If you love orchestrating complex data pipelines from multiple source systems into a well-designed data lake structure, then CGI is the place for you. The Databricks Data Architect is responsible for designing and governing an enterprise-grade Lakehouse architecture on Databricks.This role leads end-to-end solution design—from data ingestion and modeling through performance optimization, governance (Unity Catalog), reliability, and cost control—while enabling analytics, AI/ML, and self-service data capabilities at scale. In this role, you will be responsible for designing, developing, and implementing robust and scalable data architectures and ETL solutions and require deep expertise in Databricks for data processing and Lakehouse architecture. This role offers a unique blend of hands-on coding, technical leadership and strategic influence. You will inspire innovation, foster collaboration, and drive continuous improvement within your team, making a tangible impact on how our client leverages data to unlock growth and competitive advantage. If you thrive in a fast-paced, evolving landscape and are passionate about harnessing data to solve complex business challenges, this is the role for you. Growth at CGI is driven by your goals, so if you're looking for an inclusive place where you're empowered to chart your own path, then we'd love to meet you. This role is remote and open to candidates living in the United States. We are accepting applications through January 31, 2026.

Requirements

10+ years of experience in data engineering or architecture, including 5+ years of direct experience designing end-to-end solutions leveraging Databricks on cloud services, with proficiency in Apache Spark, Databricks SQL, Delta Lake & Lakehouse Architecture, Unity Catalog, Python, and Scala.
Expertise in Databricks Platform- Deep understanding of Databricks architecture, clusters, notebooks, and workspace management. Experience with Unity Catalog, Databricks Repos, Jobs API, and Workflows.
Data Engineering & ETL Development- Ability to design and implement scalable ETL pipelines using Databricks and Spark.
Cloud Platforms- Hands-on experience with Azure, AWS, or GCP integrations with Databricks.
Data Modeling- Expertise in designing logical and physical data models for analytics and reporting.
Data Governance & Security- Familiarity with Unity Catalog, role-based access control, and compliance standards.
Performance Tuning- Ability to optimize Spark jobs, cluster configurations, and storage for cost and speed.
Hands-on Development- Ability and willingness to code and troubleshoot critical issues under tight deadlines.
Demonstrated Experience- Proven track record of successfully delivering multiple complex, enterprise-scale projects leveraging Databricks, including end-to-end solution design, implementation, and optimization.

Nice To Haves

Databricks Data Engineering Professional certification
Designing and implementing data pipelines in Azure Data Factory.
Experience with DevOps principles including CI/CD, unit testing, and Agile methodologies.
Experience with metadata management, data cataloging, and data mesh domain architecture.
Exposure to Databricks migration tooling (e.g., Lakebridge) and cross-tenant/region governance strategies.

Responsibilities

Provide technical and architectural guidance on Databricks, modern data platforms, and cloud-native solutions to both clients and internal team members.
Design and implement scalable data architectures using Databricks, with hands-on experience in specific platform features such as Delta Lake, Uniform (Iceberg), Delta Live Tables, and Unity Catalog.
Lead and mentor engineering teams, fostering a culture of learning and innovation, while driving best practices in data management and performance optimization.
Engage with clients to understand their business challenges and deliver solutions that align with their goals, utilizing Databricks' capabilities to enhance outcomes.
Demonstrate hands-on technical leadership in designing and developing different components of a Data Lakehouse platform to meet client's business needs.
Deepen CGI's presence in the market by developing proposals, SOWs, and strategies to grow our footprint within existing accounts.