• Define and maintain data governance standards including access controls, data lineage, and contracts between data producers and consumers • Lead the technical direction and evolution of our data platform as we move toward an AI-first data infrastructure. You will design for AI consumption, unstructured data access, and integration with AI tooling from the ground up. • Build and scale data pipelines and architectures that make data accessible and useful to both human analysts and AI systems. • Own end-to-end design and development of scalable data pipelines, from ingestion and orchestration to transformation and delivery, using tools including AWS, Terraform, Airflow, Snowflake, dbt, Meltano, Python. • Drive data platform reliability through performance optimization, data quality monitoring, and SLA-based prioritization of our most critical data assets. • Leverage and champion AI-assisted development tools, including Claude Code, to accelerate development velocity across the team. • Mentor data engineers and analysts, raising the technical bar across the team.

Senior Aftermarket Sales Engineer, Data Centers Location: TX-Brookshire Workplace: Remote Position Contract Type: Full-Time Employment Type: Regular Job Description: Are you passionate about driving aftermarket growth in the fast-evolving data center industry while building lasting partnerships with key stakeholders? Then join us in our mission to pioneer smarter solutions for moving and transforming water, reducing energy consumption, and enhancing quality of life for people. As our new Senior Aftermarket Sales Engineer, Data Centers, you will be cultivating and managing strategic relationships with data center clients across the USA and Canada, driving aftermarket sales of spare parts and preventative maintenance services while identifying new growth opportunities within this high-demand sector. You'll be part of a diverse, supportive and inclusive culture, that celebrates our differences and puts people first by fostering growth, well-being, and a sense of belonging. What you will be doing As a key part of the Data Center Sales team, you'll create impact by Expanding Grundfos' market presence in the data center aftermarket segment by delivering tailored solutions that keep critical infrastructure running reliably. Your main responsibilities include: - Build and maintain strong, trust-based relationships with key aftermarket customers in the data center industry, understanding their technical and business needs to deliver tailored solutions - Develop and execute strategic account plans to drive aftermarket sales growth, achieve revenue targets, and expand the customer base within the data center sector - Lead negotiations and close deals with end users and purchasing customers, ensuring mutually beneficial agreements aligned with Grundfos' business objectives - Monitor market trends, competitor activities, and customer feedback to inform strategic decisions and identify areas of potential growth - Collaborate with Data Center KAMs, CSSC, Operations, Engineering, and CBS Project Managers to develop customized solutions that meet customer requirements - Provide regular updates and reports on account status, sales forecasts, and market insights to management What makes you a great fit Above all, you are a technically sharp, relationship-driven sales professional with deep knowledge of industrial or data center markets and a proven track record of growing aftermarket revenue through strategic account management. We would also imagine that you have: - Bachelor of Science in Engineering or equivalent technical/business degree - 5-10 years of industrial, commercial, or municipal sales experience with proven results - Strong technical aptitude with the ability to understand and articulate complex solutions - Valid driver's license and ability to travel up to 30%, including overnights and weekends It is a plus if you also: - Data center industry experience - Experience with CRM and business analytics tools - Understanding of profit and loss accounting and revenue flow in an organization You'll also be available for travelling up to 75 days per year. Role can be remote in Texas but preferred hybrid in Brookshire, Texas. Why you will love working here We care! Day to day, you can look forward to: - A working environment built around your needs, with flexible hours, home working opportunities and parental support. - Annual bonuses, health insurance and a strong focus on well-being activities. - Three days' additional paid leave for volunteering in your community. - Access to on-demand training and learning sessions and carefully structured programs to pursue personal and professional development opportunities. To get to know us better, follow us on LinkedIn or YouTube. Check out Meet our people to get to know some of your future colleagues and why they love working at Grundfos. The salary range for this position is $83,300.00 - $132,830.00. Individual pay will be determined based on market location and the candidate’s profile. The range listed is just one component of the total compensation and benefits package for employees. Total compensation includes paid time off, paid holidays, merit increases, bonuses, and employee stock purchase programs, etc. The salary rates are benchmarked and reflect the target for new hire salaries for the position in this region. Qualified candidates must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.

• Identify and suggest new technology to enhance data systems and support business needs • Collaborate with business analysts, Data Management teams, Data Analytics, Data Science, and other IS analysts to convert business requirements into enterprise data solutions • Design and build enterprise data storage and access solutions, integrating multiple data sources and systems • Maintain data quality, integrity, and reliability by promoting best practices • Develop formal architectural documentation based on project needs • Recommend standards to optimize performance and efficiency within the data storage ecosystem • Implement security frameworks to manage data and visualization access effectively • Build consensus between business and technical partners and understand other business units involved • Handle highly complex requests and solutions spanning IS and business functions • Design, execute, modify, and optimize data masking for integrated data sources • Lead, document, and implement aspects of information provisioning, data analysis, profiling, modeling, masking, provisioning, and R&D • Manage current and future needs concerning data design, structure, content, and inventory • Analyze, design, and support implementation for complex service requests • Research business issues and aid in developing complex data models • Conduct unit testing, including creating test cases based on requirements; possess advanced knowledge of unit and user acceptance testing • Review test plans and participate in testing to ensure deliverables meet expectations • Actively promote teamwork and continuous improvement • Practice active listening with colleagues • Communicate promptly and escalate issues to leaders or project managers as needed • Write clear, professional, and engaging business correspondence • Encourage peer review of deliverables, supporting consistent and effective documentation that aligns with team standards and templates • Coach and mentor others in the data management teams

• Design and implement reliable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured, and multi-modal data (e.g., databases, documents, APIs, events), ensuring data is AI-ready, governed, secure, and observable. • Build and scale retrieval infrastructure, including vector storage, embedding pipelines, hybrid search, and graph-based knowledge representations, while optimizing data modeling for retrieval quality. • Develop and operate agent memory systems and pipelines for AI system signals (tracing, feedback, evaluation, and usage data) to support observability and continuous improvement. • Apply data quality, validation, monitoring, and testing frameworks in production pipelines, ensuring governance, access control, lineage, and security standards are met, including safe handling of sensitive data in AI retrieval and generation workflows. • Monitor, troubleshoot, and optimize AI data pipelines and retrieval workflows for reliability, performance, and cost, with strong observability and resilient processing patterns. • Design and support evaluation workflows for AI systems, enabling offline testing, benchmarking, and continuous improvement of retrieval and agent performance over time. • Lead pragmatic platform evolution by defining clear contracts between AI services and data systems, reducing coupling, and improving developer experience.