Senior Databricks Architect

Job Details:

• Role: Senior Databricks Architect
• Require Domain exp: Insurance Domain experience is good to have.
• Location: North York, ON, Canada
• Work Model: Hybrid - 3 days in a week work from office is must, this is not initiate remote or complete remote role, find and share local candidates only who can commute easily.
• Onsite Requirement: Candidates must be available to work from the office from Day 1
• Job Type: Subcontractor (Initial Short Term and it may extend on client demand).
• Rate: CAD 70/hr All Inclusive HST and All should be included in the rate. Birlasoft will not provide any relocation assistance or any travelling/ accommodation or neither any addition expenses apart from discussed/agreed rate.

Mandatory Skills

#

Skill

Requirement

1

Databricks Data Engineering

Must have hands-on experience delivering at least one end-to-end Databricks implementation

2

Data Transformation & Pipeline Development

Experience building and managing transformation pipelines in Databricks

3

AWS Cloud Platform

Strong understanding of the AWS ecosystem; client environment is predominantly AWS

4

AWS Data Services

Working knowledge of S3, Redshift, Lake Formation, etc.

5

Apache Spark / PySpark

Strong data engineering expertise, preferably within Databricks

6

Strong Data Engineering Experience

Practical implementation experience, not just theoretical or presentation-level exposure

7

Problem-Solving & Delivery Mindset

Ability to work across technologies and drive solutions through successful delivery

Key Technical Experience:

We are looking for a Senior Databricks Architect with strong hands-on experience in:

• Databricks Data Engineering with at least one end-to-end Databricks implementation
• Data Transformation and Pipeline Development
• AWS Cloud Platform and AWS data services
• Amazon S3, Redshift, Lake Formation, etc.
• Apache Spark / PySpark
• Enterprise Data Engineering
• Data Lakes, Data Warehouses and Lakehouse architectures
• Problem-solving and end-to-end solution delivery

Preferred Experience:

• 15+ years of experience in Data & Analytics
• 5+ years of Databricks Architecture experience
• Experience with Databricks Unity Catalog, Delta Lake, Mosaic AI, Genie and Agent Bricks
• Experience in AI/GenAI, Lakehouse, Data Modernization and Advanced Analytics
• Strong consulting and stakeholder management experience
• AWS Solutions Architect certification is preferred

Role Overview:

The candidate will lead the architecture and implementation of enterprise-scale AWS Databricks data platforms, including Data Lakes, Data Warehouses and Lakehouse solutions supporting Analytics, AI and Machine Learning initiatives.

Key Responsibilities

1. Design and implement secure, scalable and highly available cloud-based solutions on AWS.
2. Lead the architecture, design and implementation of enterprise-scale data platforms leveraging Databricks on AWS.
3. Define data architecture strategy, governance frameworks, release planning and platform roadmaps.
4. Partner closely with customer stakeholders to drive data and technology modernization initiatives.
5. Provide technical leadership, customer-facing communication and solution ownership from strategy through implementation.
6. Implement Databricks Agent Bricks to enable domain-specific AI agents using enterprise data.
7. Design and implement scalable Data Lake, Data Warehouse and Lakehouse architectures.
8. Leverage Databricks Genie and AI/BI capabilities to enable natural-language analytics and self-service insights.
9. Develop large-scale data engineering and analytics solutions using Databricks, AWS and PySpark.
10. Integrate Amazon S3, AWS Lake Formation, AWS DevOps pipelines and Databricks workflows for end-to-end data and AI platform automation.
11. Integrate structured, semi-structured and unstructured data sources into enterprise Data Lakes and Data Warehouses.
12. Apply best practices in data modeling, data architecture, metadata management, data governance and data quality.
13. Evaluate and communicate the advantages and trade-offs of different cloud, analytics and AI platforms.
14. Translate business requirements into scalable AWS-based data and AI solutions.
15. Define and implement AWS cloud governance, security, compliance and operational best practices.
16. Identify opportunities to automate platform operations, deployments, monitoring and data engineering workflows.
17. Lead architecture reviews, establish technical standards, mentor engineering teams and ensure successful delivery of enterprise-scale AWS Databricks programs.

Preferred Experience:

• 12+ years in Data & Analytics with 5+ years of Databricks Architecture experience
• Databricks Unity Catalog, Delta Lake, Mosaic AI, Genie and Agent Bricks
• AWS Solutions Architect certification
• AI/GenAI, Lakehouse, Data Modernization and Advanced Analytics experience
• Strong consulting and stakeholder management experience

Please prioritize candidates who have strong hands-on Databricks + AWS experience and are comfortable working onsite 3 days per week from Day 1.

Please share relevant profiles at the earliest.