Senior Databricks Engineer with strong expertise in developing optimizing and maintaining data engineering solutions on the Databricks platform. The candidate should have deep experience with Apache Spark (PySpark) Databricks notebooks Delta Lake and Spark performance optimization. This role is focused on Spark-native data engineering rather than ETL tool development.
Must Have Skills:
Strong hands-on experience with Databricks notebooks Jobs Workflows Repos and Unity Catalog
Strong expertise in PySpark and Spark SQL
Experience building scalable Spark-based data pipelines
Strong understanding of Spark DataFrames joins aggregations window functions and distributed processing
Experience with Delta Lake (MERGE OPTIMIZE ZORDER VACUUM Change Data Feed)
Hands-on experience in Spark job performance tuning
Experience optimizing partitions shuffles caching memory usage and cluster utilization
Experience developing batch and incremental data processing pipelines
Strong programming skills in Python PySpark and SQL
Experience working on Azure Databricks AWS Databricks or GCP Databricks
Experience with Git CI/CD code reviews testing and production deployments
Implement event-driven data flows and real-time data ingestion using Apache Kafka.
Develop and integrate REST APIs for both data extraction and downstream data serving.
Monitor tune and optimize PySpark workloads for maximum performance and cost efficiency.
Communicate effectively with cross-functional stakeholders to gather requirements and translate them into scalable technical solutions.
Mentor junior developers guide architectural decisions and prepare to take on team lead responsibilities in the future. as nice to have.
Good to Have Skills:
Experience with Lakehouse and Medallion architecture
Knowledge of Data Modeling and Data Governance
Nice to Have Skills:
Experience with Delta Live Tables (DLT)
Experience mentoring teams or leading technical discussions
Experience with Photon and Databricks Asset Bundles
Experience with Cluster Policies and Workspace Administration
Design build and maintain robust batch and streaming data pipelines using Databricks and PySpark.
Extract complex data from a variety of upstream sources (databases internal/external APIs flat files) and process it into the data lake.
Architect and optimize Delta Tables utilizing the Medallion architecture (Bronze Silver Gold layers) for structured data governance.
Soft skills:
Must have strong written and verbal communication skills excellent articulation skills and experience working with client teams.
The candidate should have actively participated in and contributed to sprint planning and solution design.
Required Experience:
Senior IC
Role: Senior Azure Databricks DeveloperRole Summary:Senior Databricks Engineer with strong expertise in developing optimizing and maintaining data engineering solutions on the Databricks platform. The candidate should have deep experience with Apache Spark (PySpark) Databricks notebooks Delta Lake a...
Role: Senior Azure Databricks Developer
Role Summary:
Senior Databricks Engineer with strong expertise in developing optimizing and maintaining data engineering solutions on the Databricks platform. The candidate should have deep experience with Apache Spark (PySpark) Databricks notebooks Delta Lake and Spark performance optimization. This role is focused on Spark-native data engineering rather than ETL tool development.
Must Have Skills:
Strong hands-on experience with Databricks notebooks Jobs Workflows Repos and Unity Catalog
Strong expertise in PySpark and Spark SQL
Experience building scalable Spark-based data pipelines
Strong understanding of Spark DataFrames joins aggregations window functions and distributed processing
Experience with Delta Lake (MERGE OPTIMIZE ZORDER VACUUM Change Data Feed)
Hands-on experience in Spark job performance tuning
Experience optimizing partitions shuffles caching memory usage and cluster utilization
Experience developing batch and incremental data processing pipelines
Strong programming skills in Python PySpark and SQL
Experience working on Azure Databricks AWS Databricks or GCP Databricks
Experience with Git CI/CD code reviews testing and production deployments
Implement event-driven data flows and real-time data ingestion using Apache Kafka.
Develop and integrate REST APIs for both data extraction and downstream data serving.
Monitor tune and optimize PySpark workloads for maximum performance and cost efficiency.
Communicate effectively with cross-functional stakeholders to gather requirements and translate them into scalable technical solutions.
Mentor junior developers guide architectural decisions and prepare to take on team lead responsibilities in the future. as nice to have.
Good to Have Skills:
Experience with Lakehouse and Medallion architecture
Knowledge of Data Modeling and Data Governance
Nice to Have Skills:
Experience with Delta Live Tables (DLT)
Experience mentoring teams or leading technical discussions
Experience with Photon and Databricks Asset Bundles
Experience with Cluster Policies and Workspace Administration
Design build and maintain robust batch and streaming data pipelines using Databricks and PySpark.
Extract complex data from a variety of upstream sources (databases internal/external APIs flat files) and process it into the data lake.
Architect and optimize Delta Tables utilizing the Medallion architecture (Bronze Silver Gold layers) for structured data governance.
Soft skills:
Must have strong written and verbal communication skills excellent articulation skills and experience working with client teams.
The candidate should have actively participated in and contributed to sprint planning and solution design.