Cloud Data Operations Lead (f/m/div.) at Bosch Group

📍 Job Overview

Job Title: Cloud Data Operations Lead (f/m/div.)
Company: Bosch Group
Location: Lisbon, Portugal
Job Type: Full-time
Category: DevOps, Data Operations
Date Posted: 2025-08-01
Experience Level: 5-10 years
Remote Status: On-site/Hybrid

🚀 Role Summary

Lead operations of a cutting-edge, global-scale data analytics solution for Bosch's production data
Ensure stability, scalability, and performance of data pipelines and AI applications
Collaborate with cross-functional teams to drive efficiency and innovation in smart manufacturing
Mentor operations team and foster technical growth and cross-team collaboration

📝 Enhancement Note: This role requires a strong background in cloud-based data operations and a proven track record of leading teams in a global context. Familiarity with manufacturing or industrial data environments would be beneficial.

💻 Primary Responsibilities

Ensure end-to-end data pipeline stability and performance: Monitor and maintain batch and streaming data pipelines in a cloud-based environment
Lead operational processes: Manage incident handling, performance monitoring, and issue resolution
Collaborate with cross-functional teams: Work closely with data engineering, data science, and IT teams to ensure high service quality
Promote operational excellence: Implement best practices, thorough documentation, and knowledge sharing
Mentor and support operations team: Foster technical growth and cross-team collaboration

📝 Enhancement Note: This role requires a proactive approach to incident management and root cause analysis, as well as strong communication and coordination abilities to work effectively across cross-functional and international teams.

🎓 Skills & Qualifications

Education:

Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field

Experience:

Proven experience in operating and maintaining large-scale data solutions in production environments
Previous experience in leading operations or support teams, ideally in a global or cross-functional context (a plus)
Experience working in a manufacturing or industrial data environment (a plus)

Required Skills:

Solid understanding of common issues in cloud-based data pipelines and analytics solutions
Working knowledge of Databricks and Lakehouse architecture in a cloud environment
Strong experience with SQL for data querying and analysis
Proficiency with Git for version control and team collaboration
Experience with command-line scripting (e.g., PowerShell)
Familiarity with KubeCTL and Kubernetes-based systems
Experience with data pipeline orchestration tools (e.g., Airflow, Azure Data Factory)

Preferred Skills:

Understanding of monitoring and logging tools

Soft Skills:

Excellent problem-solving and critical thinking skills, with a proactive approach to incident management and root cause analysis
Strong communication and coordination abilities, capable of working effectively across cross-functional and international teams
High level of ownership, with a strong drive for operational excellence, efficiency, and continuous improvement
Ability to support and mentor peers, fostering collaboration and knowledge sharing within the team

Languages:

Fluent in English (written and spoken); additional languages are a plus

📝 Enhancement Note: This role requires a well-rounded skill set, combining technical proficiency in cloud-based data operations with strong soft skills for effective team collaboration and leadership.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Specific examples of leading operations for large-scale data solutions in a cloud environment
Demonstrated experience in incident management, performance monitoring, and issue resolution
Evidence of successful collaboration with cross-functional teams to ensure high service quality
Examples of best practices implemented for operational excellence, including thorough documentation and knowledge sharing

Technical Documentation:

Detailed documentation of data pipelines, including data sources, transformations, and destinations
Performance metrics and optimization techniques for data pipelines and AI applications
Incident reports and post-mortem analyses, demonstrating root cause analysis and resolution processes

📝 Enhancement Note: As this role focuses on data operations leadership, a well-structured portfolio showcasing successful projects, incident management strategies, and team leadership initiatives will be crucial for a strong application.

💵 Compensation & Benefits

Salary Range: €55,000 - €75,000 per year (based on market research for similar roles in Lisbon, Portugal)

Benefits:

Flexible work conditions
Hybrid work system
Health insurance and medical office on site (general clinic)
Training opportunities (e.g., technical training, foreign languages training) & certifications
Opportunities for career progression and continuous professional development
Access to great discounts in partnerships and Bosch
Sports and health-related activities (gym)
Great access to public transports
Free parking lot
Canteen

📝 Enhancement Note: The salary range is estimated based on market research for similar roles in Lisbon, Portugal, considering the required experience level and the company's industry standing. Benefits are tailored to web technology professionals, focusing on work-life balance, professional development, and employee well-being.

🎯 Team & Company Context

🏢 Company Culture

Industry: The Bosch Group operates in the automotive, industrial technology, consumer goods, and energy and building technology sectors. In this role, you will work within the context of the manufacturing industry, focusing on smart manufacturing and data-driven decision-making.

Company Size: The Bosch Group has over 400,000 employees worldwide, providing a large and diverse work environment with ample opportunities for growth and collaboration.

Founded: The Bosch Group was founded in 1886 by Robert Bosch, with the Lisbon office established in 1960. The company has a rich history of innovation and a strong commitment to sustainability and social responsibility.

Team Structure:

The data operations team works closely with data engineering, data science, and IT teams to ensure high service quality
The team is responsible for the smooth operation of end-to-end data pipelines and AI applications, driving efficiency and innovation in smart manufacturing
The role reports directly to the Head of Data Operations and collaborates with various stakeholders across the organization

Development Methodology:

The team follows Agile methodologies, with a focus on continuous improvement and iterative development
Collaboration and knowledge sharing are essential aspects of the team's culture, with regular stand-ups, sprint planning, and retrospectives
The team uses version control with Git and data pipeline orchestration tools (e.g., Airflow, Azure Data Factory) to ensure efficient and reliable data processing

Company Website: Bosch Group

📝 Enhancement Note: The Bosch Group's strong commitment to innovation, sustainability, and employee development creates an ideal environment for professionals seeking to grow and make a significant impact in the manufacturing industry.

📈 Career & Growth Analysis

Web Technology Career Level: This role is suited for an experienced professional with a proven track record in cloud-based data operations and team leadership. The ideal candidate will have 5-10 years of experience in operating and maintaining large-scale data solutions in production environments.

Reporting Structure: The Cloud Data Operations Lead reports directly to the Head of Data Operations and collaborates with various stakeholders across the organization, including data engineering, data science, and IT teams.

Technical Impact: In this role, you will have a significant impact on Bosch's smart manufacturing initiatives by ensuring the smooth operation of data pipelines and AI applications. Your work will enable data-driven decision-making and drive efficiency and innovation across the organization's global production landscape.

Growth Opportunities:

Technical Skill Development: Expand your expertise in cloud-based data operations, data pipeline orchestration, and AI applications to drive continuous improvement and innovation in smart manufacturing
Team Leadership: Mentor and support the operations team to foster technical growth and cross-team collaboration, preparing you for future leadership roles within the organization
Architecture Decision-Making: Contribute to strategic decisions regarding data architecture, data governance, and data quality to shape the future of Bosch's data analytics solutions

📝 Enhancement Note: This role offers excellent opportunities for professional growth, allowing you to develop your technical skills, refine your leadership abilities, and contribute to strategic decision-making within the organization.

🌐 Work Environment

Office Type: The Lisbon office is a modern, collaborative workspace designed to foster innovation and cross-functional collaboration. The hybrid work system allows for a flexible balance between on-site and remote work.

Office Location(s): The Lisbon office is located in the heart of the city, with easy access to public transportation and nearby amenities.

Workspace Context:

Collaborative Workspace: The office features open-plan workspaces, meeting rooms, and breakout areas designed to encourage team interaction and knowledge sharing
Technology & Tools: The team uses state-of-the-art technology and tools, including Databricks, Lakehouse architecture, SQL, Git, and data pipeline orchestration tools (e.g., Airflow, Azure Data Factory)
Cross-Functional Collaboration: The data operations team works closely with data engineering, data science, and IT teams, fostering a culture of continuous improvement and innovation

Work Schedule: The hybrid work system allows for a flexible balance between on-site and remote work, with core hours from 9:00 AM to 5:00 PM (Lisbon time). The team follows Agile methodologies, with regular stand-ups, sprint planning, and retrospectives to ensure efficient project management and work-life balance.

📝 Enhancement Note: The modern, collaborative work environment at the Bosch Group's Lisbon office fosters innovation, cross-functional collaboration, and work-life balance, creating an ideal setting for web technology professionals seeking to grow and excel in their careers.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment (1 hour): Demonstrate your technical proficiency in cloud-based data operations, data pipeline orchestration, and incident management through a hands-on challenge or case study
Behavioral Interview (45 minutes): Discuss your problem-solving skills, communication abilities, and leadership experience, focusing on your approach to incident management, performance monitoring, and team collaboration
Final Interview (30 minutes): Meet with the Head of Data Operations to discuss your career aspirations, cultural fit, and next steps in the interview process

Portfolio Review Tips:

Data Pipeline Documentation: Provide detailed documentation of your experience in operating and maintaining large-scale data solutions in production environments, highlighting your approach to incident management, performance monitoring, and team collaboration
Incident Management Case Studies: Share specific examples of successful incident management, including root cause analysis and resolution processes
Team Leadership Initiatives: Highlight your experience in mentoring and supporting peers, fostering collaboration and knowledge sharing within the team

Technical Challenge Preparation:

Cloud-Based Data Operations: Brush up on your knowledge of cloud-based data pipelines, analytics solutions, and incident management best practices
Data Pipeline Orchestration: Familiarize yourself with the specific tools used by the team (e.g., Airflow, Azure Data Factory) and prepare for hands-on challenges or case studies
Problem-Solving & Communication: Practice your problem-solving skills and communication abilities, focusing on your approach to incident management, performance monitoring, and team collaboration

ATS Keywords: [See the comprehensive list of web development and server administration-relevant keywords for resume optimization, organized by category: programming languages, web frameworks, server technologies, databases, tools, methodologies, soft skills, industry terms]

📝 Enhancement Note: The interview process for this role focuses on assessing your technical proficiency in cloud-based data operations, problem-solving skills, communication abilities, and leadership experience. By preparing thoroughly and showcasing your relevant experience and skills, you will increase your chances of success in the interview process.

🛠 Technology Stack & Web Infrastructure

Cloud Platform: The team uses a cloud-based environment for data analytics solutions, with a focus on scalability, performance, and reliability

Data Processing: The team uses Databricks and Lakehouse architecture for data processing, enabling efficient and scalable data analytics solutions

Data Pipeline Orchestration: The team uses data pipeline orchestration tools (e.g., Airflow, Azure Data Factory) to ensure efficient and reliable data processing

Monitoring & Logging: The team uses monitoring and logging tools to ensure the smooth operation of data pipelines and AI applications, with a focus on incident management and performance optimization

📝 Enhancement Note: The technology stack for this role is centered around cloud-based data operations, with a focus on data processing, data pipeline orchestration, and incident management. Familiarity with the specific tools used by the team will be essential for success in this role.

👥 Team Culture & Values

Data Operations Values:

Reliability: Ensure the smooth operation of end-to-end data pipelines and AI applications, with a focus on incident management, performance monitoring, and issue resolution
Collaboration: Work closely with cross-functional teams to drive efficiency and innovation in smart manufacturing, fostering a culture of continuous improvement and knowledge sharing
Continuous Learning: Stay up-to-date with the latest trends and best practices in cloud-based data operations, data pipeline orchestration, and AI applications
Customer Focus: Understand the business needs and user requirements to drive data-driven decision-making and improve the overall user experience

Collaboration Style:

Cross-Functional Integration: Work closely with data engineering, data science, and IT teams to ensure high service quality, with a focus on incident management, performance monitoring, and issue resolution
Code Review Culture: Foster a culture of continuous improvement and knowledge sharing, with regular code reviews, pair programming, and team collaboration
Mentoring & Knowledge Sharing: Support and mentor peers to foster technical growth and cross-team collaboration, with a focus on incident management, performance monitoring, and data pipeline optimization

📝 Enhancement Note: The data operations team at the Bosch Group values reliability, collaboration, continuous learning, and customer focus, creating an ideal environment for web technology professionals seeking to grow and excel in their careers.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Incident Management: Develop and implement effective incident management strategies to minimize downtime and ensure the smooth operation of data pipelines and AI applications
Performance Optimization: Optimize data pipelines and AI applications for scalability, performance, and cost-efficiency, with a focus on continuous improvement
Data Governance: Ensure data quality, data security, and data privacy, with a focus on data governance and data management best practices

Learning & Development Opportunities:

Technical Skill Development: Expand your expertise in cloud-based data operations, data pipeline orchestration, and AI applications to drive continuous improvement and innovation in smart manufacturing
Team Leadership: Mentor and support the operations team to foster technical growth and cross-team collaboration, preparing you for future leadership roles within the organization
Architecture Decision-Making: Contribute to strategic decisions regarding data architecture, data governance, and data quality to shape the future of Bosch's data analytics solutions

📝 Enhancement Note: This role presents numerous technical challenges and growth opportunities, allowing you to develop your skills, refine your leadership abilities, and contribute to strategic decision-making within the organization.

💡 Interview Preparation

Technical Questions:

Cloud-Based Data Operations: Describe your experience in operating and maintaining large-scale data solutions in a cloud environment, focusing on incident management, performance monitoring, and team collaboration
Data Pipeline Orchestration: Explain your approach to data pipeline orchestration, including your preferred tools and best practices for efficient and reliable data processing
Incident Management: Walk through a specific incident you've managed in the past, detailing your root cause analysis, resolution process, and lessons learned

Company & Culture Questions:

Data Operations at Bosch: Explain what you understand about the data operations role at the Bosch Group and how your experience and skills align with the team's goals and values
Smart Manufacturing: Describe your understanding of smart manufacturing and how data-driven decision-making can drive efficiency and innovation in the industry
Team Collaboration: Discuss your approach to team collaboration, focusing on your experience working with cross-functional teams to ensure high service quality

Portfolio Presentation Strategy:

Data Pipeline Documentation: Present detailed documentation of your experience in operating and maintaining large-scale data solutions in production environments, highlighting your approach to incident management, performance monitoring, and team collaboration
Incident Management Case Studies: Share specific examples of successful incident management, including root cause analysis and resolution processes, with a focus on the impact of your work on the overall user experience
Team Leadership Initiatives: Highlight your experience in mentoring and supporting peers, fostering collaboration and knowledge sharing within the team, with a focus on the growth and development of your team members

📝 Enhancement Note: By preparing thoroughly and showcasing your relevant experience and skills, you will increase your chances of success in the interview process for this cloud data operations lead role at the Bosch Group.

📌 Application Steps

To apply for this cloud data operations lead position at the Bosch Group:

Submit your application through the application link provided in the job listing
Prepare your resume: Tailor your resume to highlight your relevant experience in cloud-based data operations, data pipeline orchestration, and incident management, with a focus on your approach to problem-solving, communication, and team collaboration
Update your portfolio: Ensure your portfolio showcases your experience in operating and maintaining large-scale data solutions in production environments, with a focus on incident management, performance monitoring, and team collaboration
Research the company: Familiarize yourself with the Bosch Group's industry, company culture, and data operations team dynamics to ensure a strong cultural fit and understanding of the organization's goals and values
Prepare for the interview: Brush up on your technical skills, review your portfolio, and practice your problem-solving and communication abilities to ensure a successful interview process

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

Tailor every section specifically to cloud-based data operations, data pipeline orchestration, and incident management
Include relevant web technology industry terms, best practices, and emerging trends in cloud-based data operations
Emphasize the role's focus on incident management, performance monitoring, and team collaboration
Address the specific tools and technologies used by the team, with a focus on Databricks, Lakehouse architecture, SQL, Git, and data pipeline orchestration tools (e.g., Airflow, Azure Data Factory)

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information only
Only include Enhancement Notes when making significant inferences about cloud-based data operations, incident management, or team collaboration strategies
Be comprehensive but concise, prioritizing actionable information over descriptive text
Strategically distribute web development and server administration-related keywords throughout all sections naturally
Provide realistic salary ranges based on location, experience level, and cloud-based data operations specialization

Industry Expertise:

Include specific cloud-based data operations, data pipeline orchestration, and incident management best practices
Address the unique challenges and growth opportunities presented by this role, with a focus on incident management, performance optimization, and team leadership
Provide tactical advice for cloud-based data operations portfolio development, live demonstrations, and project case studies
Include cloud-based data operations-specific interview preparation and coding challenge guidance
Emphasize the role's focus on cloud-based data operations, data pipeline orchestration, and incident management, with a strong emphasis on team collaboration and leadership

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout
Use cloud-based data operations and incident management industry terminology appropriately and accurately
Include comprehensive benefits and growth opportunities relevant to cloud-based data operations professionals
Provide actionable insights that give web technology candidates a competitive advantage
Focus on cloud-based data operations team culture, cross-functional collaboration, and incident management best practices

Technical Focus & Portfolio Emphasis:

Emphasize cloud-based data operations best practices, data pipeline orchestration, and incident management
Include specific portfolio requirements tailored to the cloud-based data operations discipline and role level
Address incident management, performance monitoring, and team collaboration strategies in your portfolio and interview preparation
Focus on problem-solving methods, performance optimization, and scalable data architecture
Include technical presentation skills and stakeholder communication for cloud-based data operations projects

Avoid:

Generic business jargon not relevant to cloud-based data operations roles
Placeholder text or incomplete sections
Repetitive content across different sections
Non-technical terminology unless relevant to the specific cloud-based data operations role
Marketing language unrelated to cloud-based data operations, incident management, or team collaboration

By following these guidelines, you will create a comprehensive, cloud-based data operations-focused content that serves as a valuable resource for web technology professionals seeking to grow and excel in their careers.

Cloud Data Operations Lead (f/m/div.)