Senior Manager, Product Engineering

Siemens Energy; Maharashtra; On-site; INR 3,000,000 - 6,000,000; Full time

Benefits offered by this job

Remote work up to 2 days/week

Global distributed team

Innovative projects

Medical benefits

Time off and parental leave

Job summary

Siemens Energy is seeking a Senior Manager – Product Engineering to lead the engineering execution behind its Digital Finance transformation. You will coach engineers, review pipelines, improve test coverage, and enforce documentation standards across a global team.

The role focuses on AI-assisted and AI-generated development, quality, and scalable delivery. You will collaborate with Solution Architects and Data Architects to optimize complexity, manage technical debt, and accelerate

Qualifications

• 8+ years in software or data engineering.

Responsibilities

• Lead and develop the global product execution team, including Data Engineers, AI Engineers, and BI Developers across India, Germany, and other locations.
• Set clear performance expectations, run structured development conversations, and create individual growth plans for team members.
• Build a team culture where quality, documentation, and test coverage are embedded by default.
• Partner closely with the Scrum Master to align delivery pace with engineering rigor.
• Drive full implementation of GitLab version control across all development surfaces, including Snowflake, Power BI, Python, automations, and other tools.
• Define and enforce release management standards, including branching strategy, pull request reviews, deployment gates, run books, and production release protocols.
• Formalize testing practices across the team, including unit testing, integration testing, UAT coordination, and AI-assisted test case generation.
• Build and maintain a team handbook documenting engineering standards, tooling guidelines, and evolving ways-of-working.
• Define and track engineering health metrics such as deployment frequency, lead time, change failure rate, and mean time to recovery.
• Accelerate the team’s transition from AI-assisted to AI-generated development to compress delivery cycles from weeks to days.
• Establish AI tooling standards, defining tools, tasks, quality controls, and adoption expectations across the engineering team.
• Coach engineers on AI-assisted coding, including prompt engineering, output validation, test generation, and documentation automation.
• Measure and report the impact of AI adoption against sprint velocity improvement targets.
• Collaborate with Solution Architects on evaluating new tools, frameworks, and architectural approaches that improve speed, quality, and maintainability.
• Partner with Data Architects to align pipeline standards, data engineering practices, and Community Data Pool integration with broader enterprise data strategies.
• Contribute to sprint planning and backlog refinement by identifying technical debt, sequencing risks, and estimation gaps.
• Own production environment standards, ensuring all deployed solutions include run books, monitoring, rollback procedures, and support models.
• Lead automation triage for Alteryx and UiPath workflows, ensuring smooth migration and reporting continuity during S/4HANA go-live.
• Establish code review as a formal discipline tied to quality standards and GitLab documentation.
• Ensure security, access management, and regulatory compliance are built into development practices from the start.

Skills

DevOps practices

GitLab

CI/CD pipelines

Python

Snowflake

Power BI

AI-assisted coding

Team leadership

Agile/Scrum

Data engineering

Tools

GitLab

CI/CD tooling

Snowflake

Power BI

Streamlit

Job description

Snapshot of Your Day

As Senior Manager – Product Engineering, you will lead the engineering execution behind Siemens Energy’s Digital Finance transformation, ensuring that delivery ambition is matched by engineering rigor. Your day will involve coaching engineers, reviewing GitLab pipelines, improving test coverage, and enforcing documentation standards across the product execution team.

You will work closely with Solution Architects and Data Architects to evaluate delivery complexity, identify technical debt risks, and optimize build sequencing. At the same time, you will drive the adoption of AI-assisted and AI-generated development practices, embedding engineering standards that make delivery faster, tested, scalable, and production-ready.

Your impact goes beyond code and delivery. You will establish the engineering discipline, DevOps practices, testing frameworks, and AI-enabled ways of working that create the foundation for long-term product scalability and business value realization.

How You’ll Make an Impact

• Lead and develop the global product execution team, including Data Engineers, AI Engineers, and BI Developers across India, Germany, and other locations.
• Set clear performance expectations, run structured development conversations, and create individual growth plans for team members.
• Build a team culture where quality, documentation, and test coverage are embedded by default.
• Partner closely with the Scrum Master to align delivery pace with engineering rigor.
• Drive full implementation of GitLab version control across all development surfaces, including Snowflake, Power BI, Python, automations, and other tools.
• Define and enforce release management standards, including branching strategy, pull request reviews, deployment gates, run books, and production release protocols.
• Formalize testing practices across the team, including unit testing, integration testing, UAT coordination, and AI-assisted test case generation.
• Build and maintain a team handbook documenting engineering standards, tooling guidelines, and evolving ways-of-working.
• Define and track engineering health metrics such as deployment frequency, lead time, change failure rate, and mean time to recovery.
• Accelerate the team’s transition from AI-assisted to AI-generated development to compress delivery cycles from weeks to days.
• Establish AI tooling standards, defining tools, tasks, quality controls, and adoption expectations across the engineering team.
• Coach engineers on AI-assisted coding, including prompt engineering, output validation, test generation, and documentation automation.
• Measure and report the impact of AI adoption against sprint velocity improvement targets.
• Collaborate with Solution Architects on evaluating new tools, frameworks, and architectural approaches that improve speed, quality, and maintainability.
• Partner with Data Architects to align pipeline standards, data engineering practices, and Community Data Pool integration with broader enterprise data strategies.
• Contribute to sprint planning and backlog refinement by identifying technical debt, sequencing risks, and estimation gaps.
• Own production environment standards, ensuring all deployed solutions include run books, monitoring, rollback procedures, and support models.
• Lead automation triage for Alteryx and UiPath workflows, ensuring smooth migration and reporting continuity during S/4HANA go-live.
• Establish code review as a formal discipline tied to quality standards and GitLab documentation.
• Ensure security, access management, and regulatory compliance are built into development practices from the start.

What You Bring

• 8+ years of software engineering or data engineering experience.
• 5+ years of people management experience leading technical teams.
• Proven experience building engineering discipline in teams transitioning from informal to mature practices.
• Strong experience leading distributed and multi-geography engineering teams.
• Experience managing teams across data engineering, analytics, ML/AI engineering, or related disciplines.
• Deep expertise in DevOps practices including GitLab (or equivalent), CI/CD pipeline design, branching strategies, release management, and production monitoring.
• Strong command of testing practices including unit testing, integration testing, automated test generation, and quality gates.
• Hands‑on familiarity with Python, Snowflake, Power BI, Streamlit, and GitLab.
• Experience with Agile delivery frameworks such as Scrum or Kanban.
• Active practitioner of AI-assisted coding and development.
• Experience defining AI coding standards, quality expectations, and team-wide adoption strategies.
• Strong understanding of AI-generated development workflows, agentic coding, LLM‑based code generation, and automated testing pipelines.
• Strong collaboration skills with Solution Architects and Data Architects.
• Excellent English communication skills, both written and verbal.
• Ability to proactively identify engineering gaps and independently drive improvements.
• Strong mindset toward engineering rigor as a delivery accelerator.
• Ability to balance accountability, team development, and continuous improvement in high‑growth engineering environments.

About The Team

The Siemens Energy Transformation of Industries Digital Finance team is executing a multi‑year strategy to transform how more than 1,000 finance professionals work globally. By replacing manual consolidation and reactive reporting with automated, AI‑powered intelligence delivered through a unified platform, the team is shaping the future of finance operations. As part of this journey, you will lead a globally distributed engineering team focused on building scalable digital products and establishing engineering excellence as the foundation for sustainable transformation.

Rewards / Benefits

• Employees are eligible for remote working arrangements up to 2 days per week.
• Opportunities to work with a distributed, global team.
• Opportunities to work on and lead a variety of innovative projects.
• Medical benefits.
• Time off, paid holidays, and parental leave.