We have an exciting chance for a Senior Databricks Engineer with one of our clients.

Role: Senior Databricks Engineer

Experience: 8 to 12 Years

Location: Hyderabad

Job Responsibilities
Design and implement enterprise-scale Databricks Lakehouse architectures.
Build and optimize data pipelines using Databricks, PySpark, and cloud-native technologies.
Design Medallion Architecture (Bronze, Silver, Gold) for scalable data processing.
Implement and manage Databricks Unity Catalog governance frameworks.
Configure row-level security, data masking, lineage, and Delta Sharing.
Develop real-time and batch data processing solutions.
Build AI-ready data pipelines including embeddings, indexing, and semantic search capabilities.
Implement data quality frameworks, monitoring, alerting, and SLA tracking.
Optimize Databricks performance, storage, and cloud costs.

Required Skills
Databricks Lakehouse Platform
Delta Lake
Unity Catalog
Delta Live Tables (DLT)
Databricks Workflows
Databricks SQL
PySpark
Python
SQL
Azure Data Factory (ADF)




Azure Synapse
ADLS Gen2
Data Modeling and Lakehouse Architecture

Preferred Skills
Databricks Vector Search
MLflow
Apache Kafka / Azure Event Hub / AWS Kinesis
Structured Streaming
Delta Sharing
OpenLineage
Azure DevOps / GitHub Actions
Cloud Cost Optimization
Docker / Kubernetes
Data Governance Frameworks

Ideal Candidate
9 to 12 years of overall IT and Data Engineering experience.
Minimum 5 years of hands-on Databricks experience in production environments.
Solid expertise in designing and supporting cloud-based data platforms.
Experience with enterprise-scale Azure Data Engineering solutions.
Strong understanding of performance tuning, governance, security, and data quality frameworks.

If this prospect aligns with your experience, please share your updated resume.

We would be happy to connect and discuss the opportunity further.

Regards,

Vignesh V

Momento C

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