Sr. Databricks Developer / Lead
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Description
Position Description:
Founded in 1976, CGI is among the world's largest independent IT and business consulting services firms. With 94,000 consultants and professionals globally, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services, and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion, and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com.
Job Title: Sr. Databricks Developer / Lead
Position: LA / AC
Experience: 7+ years of experience
Job location: Bangalore / Chennai
Position ID: J0526-2138
Work Type: Hybrid
Employment Type: Full Time / Permanent
Qualification: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Looking for Databricks expert with strong data engineering skills and deep AWS cloud expertise. To lead the design, build, and deployment of data products on the Databricks Lakehouse platform, ensuring scalability, goverce, security, and business value delivery.
The role requires mastery in Databricks features, Delta Lake, AWS ecosystem integration, and modern Data Engineering best practices.
Primary Responsibilities
. Design, build, and manage data products and event driven architecture using Databricks Lakehouse principles.
. Design end-to-end data pipelines using PySpark, Databricks SQL.
. Define Data Product blueprint including domain boundaries, ownership, SLAs, documentation, quality rules.
. Implement modern ingestion frameworks using Auto Loader, Delta Live Tables, Workflows.
. Develop multi-zone medallion architecture (Bronze/Silver/Gold) using Delta Lake.
. Lead Databricks on AWS integration including S3 access, IAM roles, VPC networking.
. Implement Unity Catalog goverce frameworks, fine-grained permissions, lineage tracking.
. Drive automation DevOps practices using Git, Repos, Databricks CLI/SDK, CI/CD pipelines.
. Build and optimize Spark workloads for performance and cost control (Photon/Serverless tuning).
. Lead performance reviews, code quality checks, and data engineering guidance for teams.
. Operationalize Machine Learning and advanced analytics with MLflow/Feature Store/Model Serving.
. Monitor and enhance reliability using job monitoring, observability dashboards, alerts.
. Hands-on development of Power BI dashboards, DAX measures, data models, direct Query/Import mode
. Evaluate new Databricks features and adopt innovation into technical roadmap.
Technical Skills Required
. Strong programming experience in PySpark, SQL Python for production-grade data pipelines.
. Deep mastery in Databricks, Delta Lake, Unity Catalog, Workflows, SQL Warehouses.
. Expert knowledge of AWS services: S3, Glue, Lambda, EMR, Step Functions, CloudWatch, VPC networking.
. Experience building data products with versioning, discoverability, contracts, metadata lineage.
. Good understanding of Infra-as-Code: Terraform (workspace, clusters, UC policies, jobs, service principals).
. Strong foundation in data modeling, schema design, Lakehouse Data Mesh principles.
. Familiar with goverce security frameworks (encryption, tokenization, row/column controls).
. Experience with enterprise integrations (Power BI).
Qualifications
. 5-10 years of professional Data Engineering experience.
. Minimum 3+ years hands-on with Databricks (production scale).
. Proven experience in delivering Data Products on cloud Lakehouse platforms.
Soft Skills
. Strong ownership mindset with Data Product thinking.
. Excellent communication and ability to translate architecture for business stakeholders.
. Ability to lead engineering teams and influence architecture decisions.
. Continuous innovation mindset with focus on automation, performance reusability.
CGI is an equal opportunity employer. In addition, CGI is committed to providing accommodation for people with disabilities in accordance with provincial legislation. Please let us know if you require reasonable accommodation due to a disability during any aspect of the recruitment process and we will work with you to address your needs.
#LI-GB9
Job Title: Sr. Databricks Developer / Lead
Position: LA / AC
Experience: 7+ years of experience
Job location: Bangalore / Chennai
Position ID: J0526-2138
Work Type: Hybrid
Employment Type: Full Time / Permanent
Qualification: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Looking for Databricks expert with strong data engineering skills and deep AWS cloud expertise. To lead the design, build, and deployment of data products on the Databricks Lakehouse platform, ensuring scalability, goverce, security, and business value delivery.
The role requires mastery in Databricks features, Delta Lake, AWS ecosystem integration, and modern Data Engineering best practices.
Primary Responsibilities
. Design, build, and manage data products and event driven architecture using Databricks Lakehouse principles.
. Design end-to-end data pipelines using PySpark, Databricks SQL.
. Define Data Product blueprint including domain boundaries, ownership, SLAs, documentation, quality rules.
. Implement modern ingestion frameworks using Auto Loader, Delta Live Tables, Workflows.
. Develop multi-zone medallion architecture (Bronze/Silver/Gold) using Delta Lake.
. Lead Databricks on AWS integration including S3 access, IAM roles, VPC networking.
. Implement Unity Catalog goverce frameworks, fine-grained permissions, lineage tracking.
. Drive automation DevOps practices using Git, Repos, Databricks CLI/SDK, CI/CD pipelines.
. Build and optimize Spark workloads for performance and cost control (Photon/Serverless tuning).
. Lead performance reviews, code quality checks, and data engineering guidance for teams.
. Operationalize Machine Learning and advanced analytics with MLflow/Feature Store/Model Serving.
. Monitor and enhance reliability using job monitoring, observability dashboards, alerts.
. Hands-on development of Power BI dashboards, DAX measures, data models, direct Query/Import mode
. Evaluate new Databricks features and adopt innovation into technical roadmap.
Technical Skills Required
. Strong programming experience in PySpark, SQL Python for production-grade data pipelines.
. Deep mastery in Databricks, Delta Lake, Unity Catalog, Workflows, SQL Warehouses.
. Expert knowledge of AWS services: S3, Glue, Lambda, EMR, Step Functions, CloudWatch, VPC networking.
. Experience building data products with versioning, discoverability, contracts, metadata lineage.
. Good understanding of Infra-as-Code: Terraform (workspace, clusters, UC policies, jobs, service principals).
. Strong foundation in data modeling, schema design, Lakehouse Data Mesh principles.
. Familiar with goverce security frameworks (encryption, tokenization, row/column controls).
. Experience with enterprise integrations (Power BI).
Qualifications
. 5-10 years of professional Data Engineering experience.
. Minimum 3+ years hands-on with Databricks (production scale).
. Proven experience in delivering Data Products on cloud Lakehouse platforms.
Soft Skills
. Strong ownership mindset with Data Product thinking.
. Excellent communication and ability to translate architecture for business stakeholders.
. Ability to lead engineering teams and influence architecture decisions.
. Continuous innovation mindset with focus on automation, performance reusability.
CGI is an equal opportunity employer. In addition, CGI is committed to providing accommodation for people with disabilities in accordance with provincial legislation. Please let us know if you require reasonable accommodation due to a disability during any aspect of the recruitment process and we will work with you to address your needs.
#LI-GB9
Skills:
- AWS AI Services
- Databricks
- DevOps
- GitHub
- SQLite
Skills
- AI
- Analytics
- Automation
- AWS
- CI/CD
- CLI
- Cloud
- CloudWatch
- Data Engineering
- Data Mesh
- Data Modeling
- Data Pipelines
- Databricks
- Delta Lake
- DevOps
- Event Driven Architecture
- Git
- GitHub
- IAM
- Lakehouse
- Lambda
- Machine Learning
- Medallion Architecture
- MLflow
- Networking
- Observability
- Power BI
- PySpark
- Python
- S3
- Serverless
- Spark
- SQL
- SQLite
- Terraform
- Unity
- Unity Catalog
- VPC