Experience : Its 4-7 yrs

Key Responsibilities

Delivery & Stakeholder Management

- Drive successful delivery of workstream objectives within committed timelines.
- Partner with business stakeholders, architects, product owners, data governance teams, and engineering teams.
- Influence technical and business decisions through data-driven recommendations.
- Proactively identify risks, dependencies, roadblocks and drive resolution.
- Participate in sprint planning, technical design reviews, and release activities.

Databricks Engineering

- Design, develop, optimize, and support scalable data pipelines using Databricks.
- Implement Delta Lake, Delta Live Tables, Workflows, Structured Streaming, and Lakehouse architectures.
- Develop data ingestion, transformation, and consumption solutions.
- Build highly performant Spark applications and optimize workloads for cost and performance.
- Implement CI/CD and DevOps practices for Databricks deployments.
- Support production operations and performance tuning.

Unity Catalog & Governance

- Implement and support Unity Catalog migration and adoption.
- Define and manage data governance, access controls, lineage, data classification, and auditing.
- Design enterprise-grade security models using Unity Catalog.
- Enable governed data discovery, sharing, and collaboration across domains.
- Support metadata management, business glossary, domains, metrics, and semantic layers.

Data Sharing & Collaboration

- Design and implement secure data-sharing solutions.
- Leverage Delta Sharing, federated access, and cross-platform data integration capabilities.
- Support enterprise collaboration patterns while ensuring compliance and governance requirements.
- Evaluate and implement emerging Databricks data-serving and Lakebase integration capabilities.

AI,



Semantic Layer & Business Consumption

- Develop and support business-facing semantic models and metric views.
- Enable "Talk to Data" experiences using Databricks Genie.
- Support implementation of Unity Catalog Semantics including:
- Domains
- Business Glossaries
- Metrics
- Semantic Models
- Understand and adopt emerging Databricks capabilities including:
- Genie Ontology
- Genie Agents
- Business Semantics
- AI-powered analytics and consumption patterns

Required Technical Skills

Databricks Core

- Solid hands-on experience with:
- Azure Databricks
- Apache Spark (PySpark preferred)
- Delta Lake
- Databricks Workflows
- SQL Warehouses
- Databricks Asset Bundles
- Delta Live Tables (DLT)
- Structured Streaming

Cloud & Data Engineering

- Azure Data Lake Storage (ADLS)
- Azure Data Factory or equivalent orchestration tools
- CI/CD using Azure DevOps or GitHub Actions
- Python, SQL
- Data modeling and dimensional modeling
- Enterprise data warehouse and lakehouse concepts

Unity Catalog & Security

- Unity Catalog administration
- Data governance frameworks
- Access control design
- Data lineage and cataloging
- Row and column level security
- Regulatory and compliance considerations

Analytics & Semantic Modeling

- Semantic data models
- Metric Views
- Business KPIs and analytical modeling
- Databricks Genie
- Data serving and consumption architectures

Preferred Skills

- Experience in large-scale banking or financial services transformation programs.
- Experience with Delta Sharing and federated data access.
- Understanding of Lakebase architecture and application integration patterns.
- Familiarity with GenAI and Databricks AI capabilities.
- Experience implementing enterprise semantic layers and business ontology models.
- Experience with Agile delivery methodologies.

📌 Data Brick (Bengaluru)
🏢 Artech
📍 Bengaluru