Databricks Engineer - Senior / Lead
At a glance
Senior Data Engineering role at Blend360. Remote, India · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain data pipelines in Azure Databricks, then tune Spark jobs for speed, cost and scale
- Create ETL and ELT flows with PySpark, Spark SQL and Python across structured and semi-structured data
- Manage Delta Lake tables, including schema changes and time-travel access, and connect Databricks to ADLS Gen2
- Write SQL transformations and support analytics or machine-learning work with scientists, analysts and stakeholders
- Check data quality, validation and monitoring, while applying Azure security, access and governance practices
What you bring
- At least six years in data engineering, with practical Azure Databricks experience
- You can process data with Python and use SQL for joins, window functions and performance tuning
- Hands-on Apache Spark or PySpark work, plus experience using Delta Lake
- You understand distributed computing and Azure Data Lake Storage, and have worked with Git and Azure Data Factory
Who this fits
This senior or lead role suits an experienced engineer who wants hands-on Azure Databricks pipeline and analytics work. It is remote and based in Hyderabad.
From the employer
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.
We are looking for an experienced Azure Databricks Engineer with strong hands-on expertise in Python, SQL, and Apache Spark to design, build, and optimize scalable data pipelines and analytics solutions on the Azure cloud platform. The ideal candidate should have experience working with large datasets, distributed data processing, and modern data engineering practices.
Responsibilities
Design, develop, and maintain scalable data pipelines using Azure Databricks
Implement ETL/ELT workflows using PySpark, Spark SQL, and Python
Optimize Spark jobs for performance, cost, and scalability
Work with structured and semi-structured data (Parquet, Delta, JSON, CSV)
Build and manage Delta Lake tables (ACID, time travel, schema evolution)
Integrate Databricks with Azure Data Lake Storage (ADLS Gen2)
Develop complex queries and transformations using SQL
Collaborate with data scientists, analysts, and stakeholders to support analytics and ML use cases
Ensure data quality, validation, and monitoring
Follow best practices for security, access control, and governance in Azure
6+ years of experience in Data Engineering
Strong hands-on experience with Azure Databricks
Proficiency in Python for data processing
Strong knowledge of SQL (joins, window functions, performance tuning)
Hands-on experience with Apache Spark / PySpark
Experience working with Delta Lake
Knowledge of Azure Data Lake Storage (ADLS Gen2)
Understanding of distributed computing concepts
Experience with Git version control
Experience with Azure Data Factory
Exposure to CI/CD pipelines (Azure DevOps, GitHub Actions)
Basic understanding of data modeling
Familiarity with cloud security and RBAC in Azure
Exposure to streaming data (Spark Structured Streaming, Event Hub, Kafka)
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