Bosch Group: Sr.Data Engineering — bengaluru, India

About Bosch Group

Bosch's India activities span mobility, industrial technology, consumer goods, and energy and building technology. Its employer description identifies engineering development, manufacturing and commercial operations within that range. The group operates through multiple Indian businesses, including activities in automotive systems, software and engineering, industrial technology and home appliances. This makes Bosch a collection of related technology businesses rather than a single product operation, with different entities serving different industrial and consumer applications.

The position and its setting

Bosch Group lists Sr.Data Engineering in bengaluru, India, under reference REF291508O. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Full-time
• Employer listing date: 29 September 2026
• Contract type: Unlimited
• Legal Entity: Bosch Global Software Technologies Private Limited
• Brands: Bosch Group

Responsibilities and work described

• Job Description
• Overall"mso-spacerun:yes">
• 6– 8 years of relevant experience
• Should be flexible to adapt to project requirements needs
• Data Pipeline Development: Design, build, and optimize robust, scalable, and efficient ETL/ELT data pipelines using Python and PySpark, primarily within Azure Databricks and Azure Data Factory
• Data Ingestion & Processing: Develop and manage processes for ingesting data from various sources (e.g., transactional databases, APIs, streaming sources) and transforming it into clean, usable formats for downstream consumption
• Data Quality & Monitoring: Implement comprehensive unit and integration test coverage for data pipelines
• Establishment: and maintain monitoring, alerting, and dashboarding solutions (e.g., Grafana) for data quality, pipeline health, and performance
• Cloud Infrastructure Management (OpenShift/Azure):
• Development: and optimize complex SQL queries for data extraction, transformation, and loading
• Apply data modeling principles for efficient data storage and retrieval in SQL Server and other data stores
• Azure Ecosystem Leverage: Utilize a broad range of Azure data and analytics services, including Azure Data Factory, Azure Databricks, Azure SQL Server, Azure Key Vault, and others to build comprehensive data solutions
• Performance Optimization: Proactively identify and resolve performance bottlenecks in data pipelines and databases through query optimization, indexing strategies, and efficient data processing techniques
• Collaboration & Documentation:
• Work: closely with data scientists, analysts, and other engineering teams to understand data requirements
• Create clear and concise documentation for data pipelines, architecture, and processes

Essential requirements and candidate background

• Programming & Data Processing:proficiency in Python and PySpark for large-scale data processing and ETL development
• Data Warehousing & SQL:
• Demonstrable experience in designing, building, and maintaining robust ETL/ELT data pipelines
• Cloud Data Platform (Azure Focus):Hands-on experience with Azure Databricks
• Proficiency: core Azure Analytics Services including Azure Data Factory, Azure SQL Server, and Azure Key Vault
• DevOps & CI/CD:Experience implementing CI/CD pipelines from GitHub (including GitHub Actions) for automated testing (unit tests), build, and deployment processes
• Containerization & Orchestration:
• Familiarity and practical experience with OpenShift (setup, deployment-ready configurations, and management)
• Experience: HELM for deploying applications on Kubernetes/OpenShift
• Monitoring & Observability:
• Experience: setting up and configuring Grafana for dashboards to monitor data quality and pipeline health
• BE,MCA,M Tech

Education and qualification routes

• Degree / qualification: Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field

Preferred experience and additional strengths

• Expertise in SQL for complex querying, data manipulation, and schema design.(Optional, but highly preferred): experience in SQL optimization and performance tuning.ETL Development:
• Relevant Azure certifications (e.g., Azure Data Engineer Associate)
• Experience: real-time data processing frameworks (e.g., Kafka, Azure Event Hubs)
• Understanding: data governance, data security, and compliance best practices

Location, schedule and contract conditions

• Work arrangement: On-site
• Advertised location: bengaluru, India

Conditions requiring the complete notice

Some passages contain complex or combined conditions that have not been reduced to short eligibility statements here. Read the complete linked notice for those passages, including any alternatives, exceptions or restrictions. The concise facts above should not be treated as the full wording of every condition.

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Sr.Data Engineering vacancy is not an offer for reference REF291508O; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Bosch Group

Applications follow the official employer page linked below.

Open the official Bosch Group posting below and match the title and reference REF291508O.

Compare your qualifications and experience with the essential conditions for the bengaluru, India position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• SQL
• Kafka
• Kubernetes
• CI/CD
• Azure
• APIs
• maintenance
• compliance