Sr. Data Engineer

Overview

Our Transformation team is focused on improving business outcomes and employee experiences through step-change improvements in enterprise processes, technology, data, analytics, and AI capabilities. The Senior Data Engineer will design, build, integrate, and operate scalable data solutions across enterprise data and AI platforms (e.g. Celonis, Databricks, AWS, Azure). 

The Senior Data Engineer will translate business needs into secure, maintainable, and reusable technical solutions, with a primary focus on bringing together data from multiple enterprise sources through robust, scalable pipelines. The role will establish reliable data models, automated testing and validation, and production-ready integration patterns that enable analytics, AI, and emerging agentic workflows. The engineer will partner with cross-functional stakeholders to deliver measurable outcomes in a complex global environment. Success requires strong engineering discipline, analytical problem solving, and adaptability. 

Responsibilities

• Design, build, test, deploy, and support robust batch and streaming data pipelines that integrate and reconcile data from multiple cloud and enterprise sources using reusable, resilient patterns. 
• Develop governed data models, reusable data products, and APIs that power analytics, automation, AI, and operational applications while ensuring security, lineage, governance, and human oversight. 
• Embed automated testing and validation throughout the data pipeline lifecycle, including data-quality checks, regression testing, CI/CD, observability, production monitoring, and continuous improvement of performance and reliability. 
• Partner with business and technical stakeholders to define requirements and deliver scalable, robust solutions that drive business outcomes. 
• Work effectively and independently in Agile delivery models and clearly communicate technical decisions, risks, dependencies, and outcomes to technical and business audiences. 

Qualifications

 

• 5+ years of experience in data engineering, software engineering, data science, or a related technical field, with a bachelor's degree in Computer Science or other relevant discipline. 
• Strong software engineering foundations, including object-oriented Python, SQL, modular design, data structures, debugging, source control, code review, automated testing, and development of production-quality, maintainable code.  
• Experience designing and building robust ETL pipelines or software components that integrate, reconcile, and validate multiple data sources, supported by sound data modeling, data quality, governance, security, and lifecycle management practices.  
• Hands-on experience with enterprise application integration and workflow automation, including automated unit, integration, regression, and data-quality testing; CI/CD; orchestration; observability; monitoring; and production support. 
• Demonstrated intrinsic motivation, technical curiosity, and problem-solving ability, including learning unfamiliar technologies, debugging complex code and data issues, evaluating engineering tradeoffs, and translating requirements into scalable technical solutions. 

PREFERRED QUALIFICATIONS

• Experience with process intelligence or process mining solutions, such as Celonis. 
• Experience with supply chain processes and supporting data.