Posted 18 May, 2026
Databricks Unified Data Analytics Platform
NR Consulting - India
Bangalore, Karnataka, IN
Full Time
Reference: 26-01616-2220-1
Title: Databricks Unified Data Analytics Platform
Location: Bangalore
Exp: Minimum 12 year(s) of experience
Job Description:
Roles & Responsibilities:
• Design and build complex pipelines using Delta Lake, Auto Loader, Delta Live Tables (DLT), and deployment using Asset Bundles.
• Proven experience as a Data Architect and Data Engineer leading enterprise-scale Lakehouse initiatives.
• Expert-level understanding of modern Data & Analytics Architecture patterns including Data Mesh, Data Products, and Lakehouse Architecture.
• Excellent programming and debugging skills in Python.
• Strong experience with PySpark for building scalable and modular ETL/ELT pipelines.
• Architect data ingestion and transformation using DLT Expectations, modular Databricks Functions, and reusable pipeline components.
• Must have hands-on expertise in at least one major cloud platform: AWS, GCP, or Azure.
• Lead implementation of Unity Catalog: create catalogs, schemas, role-based access policies, lineage visibility, and data classification tagging (PII, PHI, etc.).
• Guide organization-wide governance via Unity Catalog setup: workspace linkage, SSO, audit logging, external locations, and Volume access.
• Enable cross-platform data access using Lakehouse Federation, querying live from externally hosted databases.
• Leverage and integrate Databricks Marketplace to consume high-quality third-party data and publish internal data assets securely.
• Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.
• Govern and manage Delta Sharing for securely sharing datasets with external partners or across tenants.
• Design and maintain PII anonymization, tokenization, and masking strategies using dbx functions and Unity Catalog policies to meet GDPR/HIPAA compliance.
• Architect Power BI, Tableau, and Looker integration with Databricks for live reporting and visualization over governed datasets.
• Build Databricks SQL Dashboards to enable stakeholders with real-time insights, KPI tracking, and alerts.
• Hands on Experience in applying Performance optimization techniques
• Lead cross-functional initiatives across data science, analytics, and platform teams to deliver secure, scalable, and value-aligned data products.
• Provide thought leadership on adopting advanced features like Mosaic AI, Vector Search, Model Serving, and Databricks Marketplace publishing.
• Working knowledge of DBT (Data Build Tool) is a plus.
• Strong background in data modeling and data warehousing concepts is required.
Good to Have:
1. Certifications: Databricks Certified Professional or similar certifications.
2. Machine Learning: Knowledge of machine learning concepts and experience with popular ML libraries.
3. Knowledge of big data processing (e.g., Spark, Hadoop, Hive,Kafka)
4. Data Orchestration: Apache Airflow.
5. Knowledge of CI/CD pipelines and DevOps practices in a cloud environment.
6. Experience with ETL tools like Informatica, Talend, Matillion, or Fivetran.
7. Familiarity with DBT (Data Build Tool)
Location: Bangalore
Exp: Minimum 12 year(s) of experience
Job Description:
Roles & Responsibilities:
• Design and build complex pipelines using Delta Lake, Auto Loader, Delta Live Tables (DLT), and deployment using Asset Bundles.
• Proven experience as a Data Architect and Data Engineer leading enterprise-scale Lakehouse initiatives.
• Expert-level understanding of modern Data & Analytics Architecture patterns including Data Mesh, Data Products, and Lakehouse Architecture.
• Excellent programming and debugging skills in Python.
• Strong experience with PySpark for building scalable and modular ETL/ELT pipelines.
• Architect data ingestion and transformation using DLT Expectations, modular Databricks Functions, and reusable pipeline components.
• Must have hands-on expertise in at least one major cloud platform: AWS, GCP, or Azure.
• Lead implementation of Unity Catalog: create catalogs, schemas, role-based access policies, lineage visibility, and data classification tagging (PII, PHI, etc.).
• Guide organization-wide governance via Unity Catalog setup: workspace linkage, SSO, audit logging, external locations, and Volume access.
• Enable cross-platform data access using Lakehouse Federation, querying live from externally hosted databases.
• Leverage and integrate Databricks Marketplace to consume high-quality third-party data and publish internal data assets securely.
• Experience with cloud-based services relevant to data engineering, data storage, data processing, data warehousing, real-time streaming, and serverless computing.
• Govern and manage Delta Sharing for securely sharing datasets with external partners or across tenants.
• Design and maintain PII anonymization, tokenization, and masking strategies using dbx functions and Unity Catalog policies to meet GDPR/HIPAA compliance.
• Architect Power BI, Tableau, and Looker integration with Databricks for live reporting and visualization over governed datasets.
• Build Databricks SQL Dashboards to enable stakeholders with real-time insights, KPI tracking, and alerts.
• Hands on Experience in applying Performance optimization techniques
• Lead cross-functional initiatives across data science, analytics, and platform teams to deliver secure, scalable, and value-aligned data products.
• Provide thought leadership on adopting advanced features like Mosaic AI, Vector Search, Model Serving, and Databricks Marketplace publishing.
• Working knowledge of DBT (Data Build Tool) is a plus.
• Strong background in data modeling and data warehousing concepts is required.
Good to Have:
1. Certifications: Databricks Certified Professional or similar certifications.
2. Machine Learning: Knowledge of machine learning concepts and experience with popular ML libraries.
3. Knowledge of big data processing (e.g., Spark, Hadoop, Hive,Kafka)
4. Data Orchestration: Apache Airflow.
5. Knowledge of CI/CD pipelines and DevOps practices in a cloud environment.
6. Experience with ETL tools like Informatica, Talend, Matillion, or Fivetran.
7. Familiarity with DBT (Data Build Tool)
