Data Engineer

Responsibilities

• Design, build, and evolve data platforms and analytics solutions used in production.
• Improve existing data pipelines, models, and architectures to increase robustness, scalability, and maintainability.
• Work with data generated by physical products and systems, including time-series measurement data.
• Design, implement, and evolve stable and well-defined interfaces that enable integration with other products, platforms, and systems.
• Contribute to shared architectural patterns, principles, and technical guardrails.
• Collaborate with other engineering teams to deliver actionable insights and decision support capabilities, enabling users and customers to quickly understand the state of their systems through automated analysis of complex datasets.
• Evaluate and leverage next-generation technologies-including AI-where they create clear and sustainable value.
• Required Qualifications
• Extensive experience as a Data Engineer or in a closely related engineering role, working with data platforms and analytics solutions in production environments.
• Strong engineering mindset, with experience working with data generated by physical products and systems, including time‑series and measurement data.
• Experience building and operating backend data applications or services in a cloud environment, including proficiency in web app development, working with API, and deploying cloud hosted solutions, for example on AWS.
• Experience working with time‑series and analytical data stores (e.g. InfluxDB and object storage such as S3), and integrating these with Python‑based analytics or data science workflows.
• Hands-on experience designing, building, and operating data pipelines or data platforms that are used beyond a single team or use case.
• Ability to make and explain architectural and technical decisions based on concrete constraints such as data quality, scale, performance, operability, and long-term maintenance.
• Experience evaluating and applying new technologies or techniques-including AI-based approaches-where they meaningfully improve capabilities

Requirements

• Exposure to working in industrial domains with systems generating continuous measurement data of physical properties.
• Experience supporting or operationalizing advanced analytics or automated analysis, turning analytical outputs into actionable insights for users or customers.
• Experience working across the boundary between software engineering, data engineering, and data science, enabling analytics logic to be reliably integrated into production systems.
• Familiarity with designing solutions intended for reuse, where data products, interfaces, or insights are consumed by multiple teams or systems.
• Experience communicating complex technical topics clearly across teams, and supporting others through technical guidance, reviews, and collaborative problem-solving.
• Education
• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Electrical Engineering, or a closely related technical field, or equivalent practical experience.
• Why Work at Xylem!
• Everyone's equal value
• Feel free to visit us at https://w

Additional Information

Xylem is a Fortune 500 global water solutions company dedicated to advancing sustainable impact and empowering the people who make water work every day. As a leading water technology company with 23,000 employees operating in over 150 countries, Xylem is at the forefront of addressing the world's most critical water challenges. We invite passionate individuals to join our team, dedicated to exceeding customer expectations through innovative and sustainable solutions. We are looking for an experienced Data Engineer to join Xylem Water Infrastructure R&D - Data & Insights. The role contributes to the design, evolution, and long-term sustainability of data platforms and analytics capabilities supporting R&D, field service, and customer-facing solutions. The position is suited for an engineer with substantial experience working in complex data-driven environments, who brings strong technical judgment, architectural perspective, and the ability to contribute effectively within a team of skilled professionals. The role combines hands-on technical contribution with responsibility for shaping solutions that are robust, scalable, and maintainable over time.

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