Sr. Databricks Engineer

Fa Ewjt Saasfaprod1; Pune District; Hybrid; INR 3.500.000 - 6.000.000; Vollzeit

Zusammenfassung

Fa Ewjt Saasfaprod1 is seeking a Senior Azure Databricks Data Engineer to design and optimize scalable data platforms using the Databricks Lakehouse Platform. You will lead data pipelines, collaboration with analytics teams, and implement data governance in a cloud-native environment.

The role requires 9-15 years in data engineering, 5+ years with Azure data technologies, and 4+ years with Azure Databricks/Spark.

Qualifikationen

• 9-15 years in Data Engineering and Data Warehousing.
• 5+ years hands-on Azure Data Engineering technologies.
• 4+ years hands-on Azure Databricks and Spark ecosystem.
• Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
• Experience with large-scale structured and unstructured datasets.

Aufgaben

• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services.
• Build and optimize ETL/ELT workflows for large-scale structured and unstructured data.
• Develop data models and implement data quality, validation, and governance frameworks.
• Integrate data from multiple sources into a unified Lakehouse architecture.
• Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.
• Implement security controls, access management, and data governance using Unity Catalog.
• Collaborate with business, analytics, and AI/ML teams to deliver trusted data products.
• Monitor, troubleshoot, and resolve data pipeline issues.
• Support CI/CD, DevOps, and infrastructure automation practices.
• Maintain technical documentation and best practices.

Kenntnisse

Databricks Lakehouse

Apache Spark

Delta Lake

SQL

Python

Ausbildung

Bachelor's or Master's in CS/IT/Engineering

Tools

Terraform

GitHub Actions

Azure DevOps

Snowflake

Jobbeschreibung

Job Description: Azure / Databricks Data Engineer (9-15 Years Experience) Job Title

Senior Azure Databricks Data Engineer

Experience

9-15 Years of IT Experience

Location

Hybrid

Job Summary

We are seeking a skilled Databricks Engineerwith minimum of 5+ years of hands-on in Databrickswho can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.

Key Responsibilities

• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services.
• Build and optimize ETL/ELT workflows for large-scale structured and unstructured data.
• Develop data models and implement data quality, validation, and governance frameworks.
• Integrate data from multiple sources into a unified Lakehouse architecture.
• Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency.
• Implement security controls, access management, and data governance using Unity Catalog.
• Collaborate with business, analytics, and AI/ML teams to deliver trusted data products.
• Monitor, troubleshoot, and resolve data pipeline issues.
• Support CI/CD, DevOps, and infrastructure automation practices.
• Maintain technical documentation and best practices.

Required Technical Skills Core Technologies

• Databricks Lakehouse Platform
• Apache Spark / PySpark
• Delta Lake
• SQL
• Python

Data Engineering

• ETL / ELT Development
• Data Modeling
• Data Warehousing
• Data Quality & Validation
• Streaming & Real-Time Processing

Governance & Security

• Unity Catalog
• Data Lineage
• Row-Level Security
• Access Control & Compliance
• Data Governance Frameworks

Cloud & DevOps

• Azure / AWS / GCP
• Terraform
• GitHub Actions / Azure DevOps
• CI/CD Pipelines

Analytics & AI

• Semantic Layers
• Data Products
• BI Platforms
• Machine Learning Support
• Generative AI & RAG Architectures

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
• 9-15 years of experience in Data Engineering and Data Warehousing.
• Minimum 5+ years of hands-on experience with Azure Data Engineering technologies.
• Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem.
• Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
• Experience in handling large-scale structured and unstructured datasets.
• Strong analytical, problem-solving, and troubleshooting skills.

Preferred Qualifications

• Microsoft Certified: Azure Data Engineer Associate (DP-203).
• Databricks Certified Data Engineer Associate/Professional.
• Experience with Snowflake, Power BI, or Microsoft Fabric.
• Experience in real-time streaming solutions using Kafka/Event Hubs.
• Exposure to Data Governance and Master Data Management initiatives.

Soft Skills

• Strong stakeholder management and communication skills.
• Ability to lead technical initiatives and drive architecture discussions.
• Experience working in Agile/Scrum environments.
• Excellent documentation and presentation skills.
• Strong mentoring and team leadership abilities.

Nice to Have

• Microsoft Fabric
• Power BI
• Azure Event Hubs
• Kafka
• Machine Learning data pipelines
• Data Governance tools such as Purview