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About the Role: We are looking for a highly accomplished Databricks Practice Lead to establish and grow our Databricks competency. This individual will define the technical vision, build a world-class Databricks practice, drive customer success, lead enterprise data modernization initiatives, support strategic sales pursuits, mentor architects, and create reusable accelerators. Key Responsibilities: 1. Practice Leadership: - Build and own the Databricks Practice strategy and roadmap. - Define architecture standards, coding standards, governance, and best practices. - Build reusable frameworks, accelerators, templates, and automation assets. - Hire, mentor, and develop Databricks Architects and Senior Data Engineers. - Drive competency growth and certification initiatives. 2. Technical Leadership: - Lead enterprise implementations using Databricks Lakehouse, Delta Lake, Unity Catalog, Delta Live Tables, Databricks SQL, Workflows, MLflow, Photon, Serverless Compute, and Lakehouse Federation. - Design scalable, high-performance enterprise data platforms. 3. Data Modernization: - Lead migration from Oracle, Teradata, Hadoop, Informatica, ODI, SSIS, Azure Synapse and legacy EDW platforms to Databricks. - Deliver modernization programs for HR, ERP, Finance, Supply Chain, Procurement and Customer Analytics. 4. Architecture Responsibilities: - Design Lakehouse, Data Warehouse and Data Lake solutions. - Build metadata-driven ingestion frameworks using APIs, files, ERP, CRM, Oracle Fusion, SAP, Salesforce and Workday. - Implement CDC, data quality, governance, lineage and security. 5. Cloud Expertise: - Azure: Databricks, ADF, ADLS Gen2, Synapse, Azure SQL, Key Vault. - AWS: EMR, Glue, S3, Athena, Redshift, MWAA. - GCP: BigQuery, Cloud Storage, Composer, Compute Engine. 6. Modern Data Stack: - PySpark, Spark SQL, Python, SQL - Snowflake, DBT, Microsoft Fabric - Airflow (MWAA, Composer, Astronomer) 7. Performance Optimization: - Spark optimization, Delta optimization, partitioning, Z-Ordering, incremental processing, workload and cost optimization. 8. Delivery & Client Leadership: - Lead teams of 1550 engineers. - Conduct architecture reviews and mentor technical teams. - Engage with CIOs, Enterprise Architects and business stakeholders. - Support RFPs, solutioning, PoCs and executive presentations. 9. DevOps & Governance: - Git, Azure DevOps, GitHub, Bitbucket, CI/CD, Terraform (preferred). - Unity Catalog, RBAC, Data Governance, Data Quality and Security. Required Skills: - 14+ years in Data Engineering with 6+ years on Databricks. - Strong PySpark, SQL, Python and Spark optimization. - Experience across Azure, AWS and GCP. - Hands-on expertise in Snowflake, Microsoft Fabric, DBT and Airflow. - Experience leading enterprise-scale modernization programs. Preferred Certifications: - Databricks Certified Data Engineer Professional - Databricks Certified Solution Architect - Azure Solutions Architect Expert - Azure Data Engineer Associate - SnowPro Advanced - Microsoft Fabric Analytics Engineer Ideal Candidate: - Can build and scale a Databricks Practice. - Acts as a trusted advisor for enterprise customers. - Balances deep technical expertise with leadership and pre-sales capabilities. - Possesses experience comparable to a senior enterprise architect with broad multi-cloud, Databricks, Snowflake, Fabric, DBT and Airflow expertise.

Bangalore

Hyderabad

Pune

KPI Partners - Databricks Practice Lead 

Job Description for KPI Partners - Databricks Practice Lead  in KPI Partners in  Bangalore Hyderabad Pune for (14-20) years of experience. Apply Now!

KPI Partners - Databricks Practice Lead  | iimjobs.com