GURUGRAM · FULLTIME
Senior Data Engineer
Siemens
Gurugram · onsite · Posted 35d ago
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Section · 01
About this role
A Snapshot of Your Day
As a Senior Data Engineer, you will build the trusted data foundation that enables analytics, AI and data-driven business decisions across Siemens Energy.
Working within a complex and distributed system landscape, you will discover, analyse and integrate data from multiple business domains and applications. Your focus will be on transforming fragmented data into governed, reusable and scalable data products that can be leveraged across the organisation.
You will collaborate with business stakeholders, Data & AI consultants and analytics teams to understand data requirements, explore source systems and translate business concepts into sustainable data models. Whether identifying untapped data sources, designing reusable data products or engineering scalable solutions in Snowflake, your work will help establish the foundation for future analytics, AI and business solutions.
How You'll Make An Impact
Build and evolve the Snowflake-based data platform as the foundation for analytics, AI and business solutions.
Explore and understand complex business processes, source systems and data landscapes to identify valuable data assets.
Transform fragmented data into trusted, reusable and governed data products that can be leveraged across multiple business domains.
Design and maintain scalable data models that create a common understanding of key business entities and processes.
Develop and operate reliable data pipelines that ensure high-quality and timely data availability.
Build and maintain reusable data products covering domains such as Assets, Offers, Orders, Projects, Service Plans, CSC and FS360.
Establish engineering standards, reusable frameworks and best practices that improve scalability, maintainability and reliability.
Collaborate with business and Data & AI teams to translate business requirements into sustainable and scalable data solutions.
Ensure platform reliability, performance, data quality and operational excellence.
What You Bring
A university degree in Computer Science, Data Engineering, Information Systems, Software Engineering or a related field.
Several years of experience in data engineering, analytics engineering or modern cloud-based data platforms.
Strong expertise in Snowflake or comparable cloud data platforms.
Strong SQL and data modelling skills with experience designing scalable and reusable data structures.
Experience exploring, integrating and engineering data across complex enterprise landscapes and multiple source systems.
A solid understanding of data architecture, data governance and modern data engineering principles.
Experience building reusable data products, data pipelines and scalable analytical foundations.
A structured and analytical mindset with the curiosity to investigate unfamiliar systems, discover valuable data assets and solve complex data challenges.
The ability to translate business concepts into scalable data models and technical solutions.
Experience with cloud technologies such as AWS is an advantage.
Experience working with enterprise data from platforms such as Salesforce, SAP, Teamcenter or similar business systems is an advantage.
Experience with version control systems such as Git and modern software engineering practices is an advantage.
A proactive and ownership-oriented mindset with a passion for building reliable data foundations that create long-term business value.
Strong communication skills and the ability to work effectively with both business and technical stakeholders.
Advanced English proficiency and the ability to work effectively in a global environment.
As a Senior Data Engineer, you will build the trusted data foundation that enables analytics, AI and data-driven business decisions across Siemens Energy.
Working within a complex and distributed system landscape, you will discover, analyse and integrate data from multiple business domains and applications. Your focus will be on transforming fragmented data into governed, reusable and scalable data products that can be leveraged across the organisation.
You will collaborate with business stakeholders, Data & AI consultants and analytics teams to understand data requirements, explore source systems and translate business concepts into sustainable data models. Whether identifying untapped data sources, designing reusable data products or engineering scalable solutions in Snowflake, your work will help establish the foundation for future analytics, AI and business solutions.
How You'll Make An Impact
Build and evolve the Snowflake-based data platform as the foundation for analytics, AI and business solutions.
Explore and understand complex business processes, source systems and data landscapes to identify valuable data assets.
Transform fragmented data into trusted, reusable and governed data products that can be leveraged across multiple business domains.
Design and maintain scalable data models that create a common understanding of key business entities and processes.
Develop and operate reliable data pipelines that ensure high-quality and timely data availability.
Build and maintain reusable data products covering domains such as Assets, Offers, Orders, Projects, Service Plans, CSC and FS360.
Establish engineering standards, reusable frameworks and best practices that improve scalability, maintainability and reliability.
Collaborate with business and Data & AI teams to translate business requirements into sustainable and scalable data solutions.
Ensure platform reliability, performance, data quality and operational excellence.
What You Bring
A university degree in Computer Science, Data Engineering, Information Systems, Software Engineering or a related field.
Several years of experience in data engineering, analytics engineering or modern cloud-based data platforms.
Strong expertise in Snowflake or comparable cloud data platforms.
Strong SQL and data modelling skills with experience designing scalable and reusable data structures.
Experience exploring, integrating and engineering data across complex enterprise landscapes and multiple source systems.
A solid understanding of data architecture, data governance and modern data engineering principles.
Experience building reusable data products, data pipelines and scalable analytical foundations.
A structured and analytical mindset with the curiosity to investigate unfamiliar systems, discover valuable data assets and solve complex data challenges.
The ability to translate business concepts into scalable data models and technical solutions.
Experience with cloud technologies such as AWS is an advantage.
Experience working with enterprise data from platforms such as Salesforce, SAP, Teamcenter or similar business systems is an advantage.
Experience with version control systems such as Git and modern software engineering practices is an advantage.
A proactive and ownership-oriented mindset with a passion for building reliable data foundations that create long-term business value.
Strong communication skills and the ability to work effectively with both business and technical stakeholders.
Advanced English proficiency and the ability to work effectively in a global environment.
Sourced from foundit
Section · 02
Skills
SAPdata architectureamazon web servicesData modellingCloud Data PlatformsSQLData GovernancesalesforceSnowflakeTeamcentermodern software engineering practicesData PipelineGIT
Section · Company
About Siemens
Siemens
Industrial Automation
9.8k+
employees
1867
159 years old
Mumbai, Maharashtra
India
About
Siemens is a strong partner, technological pioneer, and responsible employer. Electrification, automation, and digitalization require innovative solutions.
Industries
Industrial AutomationUrban TransportSemiconductorsElectronics ManufacturingSoftware ProductElectrical Equipment
Employee ratings
5,809 reviews
3.9/ 5
Culture
3.9
Career growth
3.1
Work-life
4.0
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