Role Description Join our Global Professional Services team as a Lead Data Engineer, where you will be instrumental in bridging the gap between client needs, business objectives, and cutting-edge technology solutions, particularly supporting our new Private Cloud clients. This role is for more than just a service provider; we are seeking a consultant-minded go-getter who is client-obsessed, a liquid thinker who thrives at pace, and is bold and brave in challenging the status quo. We are a team that values being part of a successful business and building partnerships based on trust, deep knowledge, respect, and unwavering support. We are passionate about technology, data, and AI and how it can be leveraged to solve our clients' most pressing business challenges. You will be a key player in understanding our clients' world, becoming their trusted partner, and proactively identifying opportunities for innovation and efficiency. Curiosity, accountability, and a positive, questioning mindset are at the core of our team's DNA – we don't just aim to meet expectations, we strive to exceed them. You will work collaboratively with global Circana teams, acting as the vital link to ensure seamless, unified support and strategic technological partnership for our clients. In this role, we are seeking a skilled and motivated Data Engineer to join a growing Global Team based in the UK. You will be responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform. You will leverage your expertise in PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads, ensuring data quality, efficiency, and scalability. If you have a passion for Data Engineering and a desire to make a significant impact, we encourage you to apply! Duties & Responsibilities - Data Engineering & Data Pipeline Development - Design, develop, and optimize scalable DATA workflows using Python, PySpark, and Airflow - Implement real-time and batch data processing using Spark - Enforce best practices for data quality, governance, and security throughout the data lifecycle - Ensure data availability, reliability, and performance through monitoring and automation - Cloud Data Engineering - Manage cloud infrastructure and cost optimization for data processing workloads - Implement CI/CD pipelines for data workflows to ensure smooth and reliable deployments - Big Data & Analytics - Build and optimize large-scale data processing pipelines using Apache Spark and PySpark - Implement data partitioning, caching, and performance tuning for Spark-based workloads - Work with diverse data formats (structured and unstructured) to support advanced analytics and machine learning initiatives - Workflow Orchestration (Airflow) - Design and maintain DAGs (Directed Acyclic Graphs) in Airflow to automate complex data workflows - Monitor, troubleshoot, and optimize job execution and dependencies - Team Leadership & Collaboration - Lead a team of data engineers, providing technical guidance and mentorship - Foster a collaborative environment and promote best practices for coding standards, version control, and documentation Qualifications - Client-facing role, so strong communication and collaboration skills are vital (Ideally gained in a Consulting organisation) - 8+ years of experience in data engineering with expertise in Azure, PySpark, Spark, and Airflow - Strong programming skills in Python, SQL with the ability to write efficient and maintainable code - Deep understanding of Spark internals (RDDs, DataFrames, DAG execution, partitioning, etc.) - Experience with Airflow DAGs, scheduling, and dependency management - Knowledge of Git, Docker, Kubernetes, Terraform, and apply best practices of DevOps for CI/CD workflows - Excellent problem-solving skills and ability to optimize large-scale data processing - Experience in leading teams and working in Agile/Scrum environments - A proven track record of working effectively with global remote teams Bonus Points - Experience with data modeling and data warehousing concepts - Familiarity with data visualization tools and techniques - Knowledge of machine learning algorithms and frameworks What are we looking for? - An authentic optimist with a genuine passion for solving problems and driving progress - Intensely curious – you love to understand the 'why' and 'how' behind things, especially when it comes to technology and client challenges - Highly accountable for your actions, your deliverables, and the success of your clients - Comfortable and adept at building strong, professional relationships with both external clients and internal technical and business teams - Deeply committed to giving your best for your team and ensuring our technology solutions exceed client expectations - Confident in making informed decisions, weighing options and considering the technical and business implications - Highly organised, with meticulous attention to detail in managing documentation, communication, and time - Passionate about technology, Data, AI, and their application in solving real-world business problems - Previous experience translating client requirements into technical specifications - Previous experience building relationships with clients

• Diseñar y mantener modelos de datos analíticos. • Desarrollar y optimizar procesos ETL y pipelines de datos. • Construir soluciones de reporting y cuadros de mando en Power BI. • Trabajar junto a negocio para entender requisitos funcionales.

• Responsible for designing, building, and delivering modern Data & AI solutions on Microsoft Azure • Work closely with clients and internal delivery teams to develop scalable, production-ready data platforms • Contribute across the full project lifecycle including development, testing, deployment, optimization, and client collaboration • Partner with solution architects, project teams, and customer stakeholders to implement modern lakehouse and data engineering patterns using Microsoft technologies

• Responsible for designing, building, and delivering modern Data & AI solutions on Microsoft Azure • Work closely with clients and internal delivery teams to develop scalable, production-ready data platforms that enable analytics, reporting, operational intelligence, and AI workloads • Contribute across the full project lifecycle including development, testing, deployment, optimization, and client collaboration • Partner with solution architects, project teams, and customer stakeholders to implement modern lakehouse and data engineering patterns using Microsoft Fabric, Azure, and Databricks technologies • Support a wide range of customer environments across commercial and public sector organizations