Bangalore, Karnataka, India
Live, first seen by us 84 days agoWork setup in the employer’s posting: hybridFrom the employer’s posting
We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform.
We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform.
Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark.
Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers.
Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features.
We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.
Key Responsibilities Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark. Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers.
Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark. Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers. Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features.
Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers. Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features. Create, monitor, and optimize Delta Live Tables (DLT) pipelines.
strong expertise in Databricks, PySpark, and SQL
Delta Lake Delta Live Tables (DLT)
Structured Streaming Auto Loader
Lakehouse Data Modeling
Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.
Qualifications - Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline. - Proven experience in designing and implementing cloud-based data engineering solutions and scalable data pipelines.
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Role Overview We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization. Key Responsibilities
- Establish and enforce data governance, security, and access controls using Unity Catalog. - Optimize Spark jobs, SQL queries, and overall platform performance to ensure efficiency and scalability. - Collaborate with cross-functional teams, including data analysts, architects, and business stakeholders, to deliver high-quality data solutions.
- Auto Loader - SQL - Lakehouse Data Modeling
Key Technologies Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI Specialization
Key Technologies Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI Employment type
- Microsoft Fabric AWS Ecosystem - AWS Glue
AWS Ecosystem - AWS Glue - AWS Lambda
- AWS Glue - AWS Lambda - AWS Step Functions
- AWS Lambda - AWS Step Functions Data Engineering & Integration
Preferred Skills (Good to Have) Azure Ecosystem - Azure Data Factory (ADF)
Azure Ecosystem - Azure Data Factory (ADF) - Azure Synapse Analytics
- Azure Data Factory (ADF) - Azure Synapse Analytics - Microsoft Purview
GCP - BigQuery Qualifications
Primary Skills Databricks Engineer Role Overview
Key Responsibilities - Design, develop, and maintain end-to-end data pipelines using Databricks and PySpark. - Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers.
- Develop and manage real-time data processing solutions using Structured Streaming. - Orchestrate, schedule, and monitor data workflows using Databricks Workflows. - Design and implement Lakehouse data models to support reporting, analytics, and business intelligence requirements.
Required Skills (Must Have) - Databricks Platform - Delta Lake
- Unity Catalog - Databricks Workflows - PySpark and Apache Spark
Specialization - Databricks Engineering: Lead Data Engineer Job requirements
Job requirements Databricks Engineer Role Overview
- Apache Airflow - DBT - Fivetran
- Build and implement Lakehouse architectures utilizing Bronze, Silver, and Gold data layers. - Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features. - Create, monitor, and optimize Delta Live Tables (DLT) pipelines.
- Develop and manage Delta Lake solutions with ACID transactions, schema enforcement, and data reliability features. - Create, monitor, and optimize Delta Live Tables (DLT) pipelines. - Implement scalable and efficient data ingestion processes using Auto Loader.
- Databricks Platform - Delta Lake - Delta Live Tables (DLT)
- Delta Lake - Delta Live Tables (DLT) - Unity Catalog
- DBT - Fivetran - Informatica
- Alation GCP - BigQuery
Streaming & Analytics - Apache Kafka - Power BI
- Apache Kafka - Power BI Data Governance
- Databricks Workflows - PySpark and Apache Spark - Structured Streaming
Data Engineering & Integration - Apache Airflow - DBT
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.
Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI
We are seeking a highly skilled Databricks Engineer to design, develop, and optimize scalable data engineering and analytics solutions on the Databricks Lakehouse Platform. The ideal candidate will possess strong expertise in Databricks, PySpark, and SQL, with hands-on experience building batch and real-time data pipelines, implementing Lakehouse architectures, and ensuring data governance and performance optimization.
Databricks | PySpark | Apache Spark | Delta Lake | Delta Live Tables (DLT) | Unity Catalog | Structured Streaming | Auto Loader | SQL | Lakehouse Architecture | Azure | AWS | Airflow | Kafka | Power BI
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Bangalore, Karnataka, India
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