ETL Data Lead Developer

Overview

Talent Acquisition EMEA | Complexity into clarity

At Circana, we are committed to continuous learning and growth, invite feedback, and celebrate achievements in an environment that supports work-life balance. We are a global company that values inclusivity and belonging, embracing diverse backgrounds, skills, and perspectives to foster a stronger, more innovative environment for employees, clients, and communities. We strive to let you bring your full self to work.

Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®, based on current employee experiences. Learn more at

What is the role & team

Join our Global Professional Services team as a Lead Data Engineer. You will bridge client needs, business objectives, and technology solutions, particularly supporting our new Private Cloud clients. This role seeks a consultant-minded go-getter who is client-obsessed, a liquid thinker, thrives at pace, and is bold in challenging the status quo. We value trust, deep knowledge, respect, and unwavering support, and we work to build partnerships that drive business success. We are passionate about technology, data, and AI and how they can solve clients’ most pressing challenges. Curiosity, accountability, and a positive, questioning mindset are central to our team’s DNA. You will work with global Circana teams to ensure seamless, unified support and strategic technological partnership for our clients. In this role, you will join a growing Global Team based in the UK, responsible for designing, building, and maintaining robust data pipelines and infrastructure on the Azure cloud platform, leveraging PySpark, Apache Spark, and Apache Airflow to process and orchestrate large-scale data workloads with a focus on data quality, efficiency, and scalability.

Key Responsibilities

• 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 workloads to ensure smooth and reliable deployments
• Big Data & Analytics : Build and optimize large-scale data processing pipelines using Spark and PySpark
• Implement data partitioning, caching, and performance tuning for Spark-based workloads
• Work with diverse data formats (structured and unstructured) to support analytics and machine learning initiatives
• Workflow Orchestration (Airflow) : Design and maintain DAGs to automate complex data workflows
• Monitor, troubleshoot, and optimize job execution and dependencies
• 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

Required Skills & Experience

Bonus Points

What we are looking for

Seniority level

Employment type

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Industries

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