Senior Azure Databricks Data Engineer

Experience

Location

Hybrid

Job Summary

We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who 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