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Salary
≈ $21k – $44k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 8, 2026. Siemens scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Siemens is a German technology conglomerate founded in Berlin in 1847 by Werner von Siemens around a telegraph that indicated letters rather than Morse code. After a decade of divestments it now concentrates on industry, infrastructure, transport and healthcare, supplying factory automation and control systems, building and grid technology, trains and signalling, and the Teamcenter and NX design software acquired through a long run of software purchases. The Siemens Xcelerator platform ties hardware to software and digital twins, and the group retains a majority stake in the separately listed medical imaging company Siemens Healthineers.

A Snapshot of Your Day

As a Senior Finance Data Engineer, you will build and evolve the trusted data foundation that powers financial planning, reporting, analytics, and AI use cases across the global Grid Technology Services Finance organization.

Working in a complex enterprise environment, you will engineer scalable data products and pipelines that integrate financial and operational data from multiple source systems including SAP and other enterprise platforms. Your focus will be on transforming fragmented data into trusted, governed, and reusable assets that enable finance teams to make better and faster decisions.

You will collaborate closely with finance experts, digital finance specialists, and IT teams to understand business requirements and translate them into sustainable data models and engineering solutions. While finance domain knowledge is valuable, we are primarily looking for strong data engineers who are curious about business processes and motivated to learn the financial context behind the data they manage.

How You'll Make an Impact

As part of the Digital Finance team, you will:

  • Design, build, and operate scalable data pipelines across finance and enterprise systems.
  • Develop and maintain Snowflake-based data solutions that serve as the foundation for reporting, planning, analytics, and AI use cases.
  • Transform complex and fragmented source data into trusted, reusable, and governed data products.
  • Design and maintain scalable data models representing key financial and operational business entities.
  • Integrate data from SAP and other enterprise platforms into modern analytics and planning solutions.
  • Establish engineering standards, reusable frameworks, and best practices for finance data products.
  • Improve data quality, reliability, observability, and governance across the finance data landscape.
  • Support the modernization of finance reporting and planning platforms through sound data engineering principles.
  • Collaborate with finance experts and business stakeholders to translate business concepts into scalable technical solutions.
  • Analyze complex data flows and identify opportunities for automation, standardization, and simplification.
  • Drive continuous improvements in platform performance, maintainability, and operational excellence.
  • Contribute to the ongoing digital transformation of the GT SV Finance organization.

What You Bring

  • Required university degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related field.
  • Several years of experience in data engineering, analytics engineering, or modern cloud-based data platforms.
  • Strong SQL skills and experience working with large-scale enterprise datasets.
  • Hands-on experience with Snowflake or comparable cloud data platforms.
  • Experience designing and implementing scalable data models and data pipelines.
  • Strong understanding of data warehousing, data architecture, and modern data engineering principles.
  • Experience integrating data across multiple enterprise systems and technologies.
  • Experience building trusted, reusable, and governed data products.
  • Strong analytical and problem-solving skills with the ability to navigate complex data landscapes.
  • Ability to translate business requirements into scalable technical solutions.
  • Experience with Git and modern software engineering practices.
  • Excellent communication skills and the ability to collaborate effectively with business and technical stakeholders.
  • Advanced English proficiency.

Nice to Have

  • Experience working with SAP data, particularly finance-related datasets.
  • Experience with financial planning, reporting, or controlling processes.
  • Exposure to planning platforms such as Jedox, SAP Analytics Cloud (SAC), or similar solutions.
  • Knowledge of cloud platforms such as AWS.
  • Experience supporting analytics, reporting, or AI use cases.
  • Familiarity with finance data structures and master data concepts.

Why You Should Join Us

This role offers the opportunity to:

  • Build the finance data foundation for a global business.
  • Work at the intersection of modern data engineering, analytics, and finance transformation.
  • Develop expertise in enterprise-scale financial and operational data.
  • Shape the future architecture of finance data products and platforms.
  • Collaborate with finance experts who will help you learn the business domain while you bring technical engineering expertise.
  • Contribute to AI and advanced analytics initiatives built on trusted finance data.
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