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Data Engineer

Bangalore, Indien

Pay
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Work setting
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Apply at Mercedes-Benz Group

What you’ll work on

Full posting
  • Design 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

From the employer’s posting
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.

Tools in this posting

  • Python
  • SQL
  • Azure
  • Databricks
  • Delta Lake
  • PySpark
Source — Tool mentions in context
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.

Posting record

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Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier listing.

Status in our records
Live
First seen by us
Oct 16, 2026 · 8 days ago
Recorded sightings
51
Last seen by us
Oct 24, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on jobs.mercedes-benz.com. The employer’s form will show what is required.

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Job description

View original posting ↗

Aufgaben

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.

 

Qualifikationen

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

Source details

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Location & working pattern

Bangalore, Indien

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