Bangalore, Indien
Live, first seen by us 28 days agoDesign and maintain batch and real-time data pipelines into Azure
Build Bronze, Silver and Gold layers using Azure Databricks and Delta tables
Combine data sources into aggregate tables, views and models for reporting
Automate data workflows on weekly, monthly and ad-hoc schedules
Monitor and optimize pipelines for performance, scalability and cost
Design, build, and maintain scalable batch/ real-time data pipelines
Implement and manage the Medallion Architecture (Bronze, Silver, Gold layers) using Azure Databricks and Delta tables.
Combine multiple data sources to create optimized aggregate tables, views, and data models
Automate data workflows and pipelines on weekly/monthly/ad-hoc schedules
Continuously monitor, troubleshoot, and optimize data pipelines for performance, scalability, and cost-efficiency.
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Cloud & Big Data Stack: Strong expertise working with large volumes of data within Microsoft Azure. Deep hands-on experience with Azure Databricks, Delta Tables, and modern Azure components. Programming & Querying: Advanced working knowledge of Python and PySpark for data transformation and distributed computing. Expert-level SQL skills with strong understanding of data warehousing concepts, database schemas, and data modeling. Soft Skills & Independence: A self-starter with a proven track record of working independently to design, tune, and deliver high-performance tables and views.
Job Summary We are looking for a hands-on, self-driven Data Engineer with 4-7 years of experience to join our team. In this role, you will be the driving force behind our cloud data infrastructure, responsible for onboarding multiple data sources and building robust, scalable data pipelines using the Medallion Architecture on Microsoft Azure. You will collaborate closely with data scientists, analysts, and cross-functional squads to power downstream reporting, analytics, and machine learning initiatives. Key Responsibilities
Key Responsibilities Data Ingestion & Pipeline Development: Design, build, and maintain scalable batch/ real-time data pipelines to onboard, clean, transform, and integrate complex data sources into the Azure Cloud. Implement and manage the Medallion Architecture (Bronze, Silver, Gold layers) using Azure Databricks and Delta tables. Data Modeling & Aggregation: Combine multiple data sources to create optimized aggregate tables, views, and data models for downstream reporting and analytics applications. Automate data workflows and pipelines on weekly/monthly/ad-hoc schedules to ensure seamless data delivery.
Experience: Minimum 4 years of hands-on professional experience in data warehousing, ETL/ ELT design, and building enterprise data pipelines. Cloud & Big Data Stack: Strong expertise working with large volumes of data within Microsoft Azure. Deep hands-on experience with Azure Databricks, Delta Tables, and modern Azure components. Programming & Querying: Advanced working knowledge of Python and PySpark for data transformation and distributed computing. Expert-level SQL skills with strong understanding of data warehousing concepts, database schemas, and data modeling.
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Yes. We’ve followed 4 other Data Engineer jobs there since June 2026. All 4 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 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.
Job Summary
We are looking for a hands-on, self-driven Data Engineer with 4-7 years of experience to join our team. In this role, you will be the driving force behind our cloud data infrastructure, responsible for onboarding multiple data sources and building robust, scalable data pipelines using the Medallion Architecture on Microsoft Azure. You will collaborate closely with data scientists, analysts, and cross-functional squads to power downstream reporting, analytics, and machine learning initiatives.
Key Responsibilities
Data Ingestion & Pipeline Development: Design, build, and maintain scalable batch/ real-time data pipelines to onboard, clean, transform, and integrate complex data sources into the Azure Cloud. Implement and manage the Medallion Architecture (Bronze, Silver, Gold layers) using Azure Databricks and Delta tables.
Data Modeling & Aggregation: Combine multiple data sources to create optimized aggregate tables, views, and data models for downstream reporting and analytics applications. Automate data workflows and pipelines on weekly/monthly/ad-hoc schedules to ensure seamless data delivery.
Collaboration & Optimization: Partner closely with data engineers and data scientists across squads to feature-engineer tables and views that support advanced analytics use cases. Continuously monitor, troubleshoot, and optimize data pipelines for performance, scalability, and cost-efficiency.
Best Practices & Governance: Act as an advocate for engineering best practices, including code modularity, documentation, error handling, and data quality checks.
Required Qualifications & Skills
Experience: Minimum 4 years of hands-on professional experience in data warehousing, ETL/ ELT design, and building enterprise data pipelines.
Cloud & Big Data Stack: Strong expertise working with large volumes of data within Microsoft Azure. Deep hands-on experience with Azure Databricks, Delta Tables, and modern Azure components.
Programming & Querying: Advanced working knowledge of Python and PySpark for data transformation and distributed computing. Expert-level SQL skills with strong understanding of data warehousing concepts, database schemas, and data modeling.
Soft Skills & Independence: A self-starter with a proven track record of working independently to design, tune, and deliver high-performance tables and views.
Preferred / Good-to-Have Skills
Experience working with automotive sales and marketing data domains.
Practical understanding of Agile/Scrum methodologies and cross-functional team collaboration.
Familiarity with CI/CD tools or data orchestration frameworks
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Bangalore, Indien
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