Role : Databricks Architect

- Lead architecture, design, and implementation of data lakehouse solutions using Databricks, Delta Lake, Unity Catalog, and Apache Spark.

- Define and enforce architectural best practices for data ingestion, ETL/ELT processing, transformation, governance, and analytics.

- Oversee the deployment, scaling, configuration, and cost optimization of Databricks environments (across Azure, AWS, or GCP).

- Design high-availability, resilient pipelines for both streaming and batch data processing at enterprise scale.

- Implement and manage data governance, privacy, and lineage (Unity Catalog, fine-grained access controls, encryption, audit logging).

- Guide teams in implementing CI/CD, version control, automated testing, and infrastructure-as-code for Databricks jobs and notebooks.

- Collaborate with engineers, analysts, and data scientists to integrate advanced analytics, ML, and BI into unified data platforms.

- Lead performance tuning, cluster optimization, and job scheduling for efficient and cost-effective processing.

- Review and mentor technical team members and enforce standards via code/architecture reviews.

- Monitor industry trends, identify new features, and proactively recommend improvements to platform reliability and cost