Data Engineer - Python PySpark

Let’s be unstoppable together!

Circana is a leading provider of technology, AI, and data solutions for consumer packaged goods companies, manufacturers, and retailers. Our predictive analytics and Liquid Data® platform help clients measure market share, uncover consumer behavior, and drive growth—powered by six decades of expertise and an expansive, high-quality data set.

At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives.  We’re a global company dedicated to fostering inclusivity and belonging. We value and celebrate the unique experiences, cultures, and viewpoints that each individual brings. By embracing a wide range of backgrounds, skills, expertise, and beyond, we create a stronger, more innovative environment for our employees, clients, and communities. With us, you can always 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®. This prestigious award is based entirely on what current employees say about their experience working at Circana. Learn more at www.circana.com.

What will you be doing?

We are seeking a seasoned Data Engineer to lead the development of scalable data solutions in a cloud-native environment. This role involves designing robust data pipelines, optimizing data warehouse performance, and working with in-house tools to support advanced analytics and business intelligence initiatives.

Job Responsibilities

• Design, develop, and optimize ETL/ELT pipelines using PySpark, Python, and SQL.
• Architect and implement data warehouse solutions on Cloud platforms (AWS, Azure, GCP).
• Collaborate with cross-functional teams to understand data requirements and deliver high-quality solutions.
• Learn and work extensively with in-house data tools and frameworks, contributing to their enhancement and integration.
• Ensure data quality, governance, and security across all data assets.
• Drive performance tuning, cost optimization, and automation of data workflows.
• Participate in Agile ceremonies, code reviews, and technical design discussions.
  
  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 2–4 years of experience in data engineering, with a strong focus on cloud-based data solutions.
• Proficiency in Python, PySpark, and SQL for data processing and transformation.
• Hands-on experience with Cloud platforms (AWS, Azure, or GCP) and their data services.
• Solid understanding of data warehousing concepts, dimensional modeling, and data architecture.
• Experience with version control (Git), CI/CD pipelines, and Agile methodologies.
• Ability to quickly learn and adapt to internal tools and technologies.
• Experience with orchestration tools like Apache Airflow,
• Knowledge of data visualization tools (e.g., Power BI, Tableau).
• Strong communication and leadership skills.