Candidate Must have 15+ years of experience
Very strong experience with Databricks
We are seeking an experienced Data Architect – Databricks to lead the design, implementation, and optimization of enterprise-scale data and AI solutions on the Databricks Lakehouse Platform. The ideal candidate will work closely with client stakeholders, data engineering teams, and business leaders to deliver scalable, secure, and high-performance data analytics and machine learning solutions.
The RSA will serve as the trusted technical advisor, driving cloud data modernization initiatives and ensuring successful adoption of Databricks across the organization.

Key Responsibilities
Act as the primary technical advisor for Databricks implementations and customer engagements.
Design and implement scalable Lakehouse architectures using Databricks.
Build and optimize ETL/ELT pipelines using Apache Spark and Databricks.
Collaborate with data engineers, data scientists, analysts, and business stakeholders to translate business requirements into technical solutions.
Develop data ingestion, transformation, and orchestration workflows.
Optimize Spark jobs for performance, scalability, and cost efficiency.
Implement Delta Lake best practices including ACID transactions, schema evolution, and time travel.
Design secure data platforms with Unity Catalog, role-based access control, and governance policies.
Support migration of legacy data warehouses and Hadoop environments to Databricks.
Guide CI/CD implementation and Infrastructure as Code for Databricks deployments.
Troubleshoot production issues and provide architectural guidance.
Mentor engineering teams on Databricks best practices.
Stay current with Databricks product updates and cloud-native technologies.

Required Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
10+ years of experience in Data Engineering, Big Data, or Cloud Data Architecture.
4+ years of hands-on experience with Databricks.
Strong expertise in Apache Spark (PySpark/Scala/Spark SQL).
Experience with Delta Lake and Lakehouse Architecture.
Strong SQL programming skills.
Experience with cloud platforms:
Azure (Preferred)
AWS
GCP
Experience with cloud storage:
ADLS Gen2
Amazon S3
Google Cloud Storage
Experience building batch and streaming data pipelines.
Strong understanding of data modeling and data warehousing concepts.
Hands-on experience with Git and CI/CD pipelines.
Experience with REST APIs and integration services.- Experience contributing to portfolio rationalization and/or technical debt remediation initiatives at an enterprise level