Company description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value. Overview Publicis Sapient is looking for Python developers to join our team of bright thinkers and enablers. You will use your problem-solving skills, craft & creativity to design and develop infrastructure interfaces for complex business applications. We are on a mission to transform the world, and you will be instrumental in shaping how we do it with your ideas, thoughts, and solutions. Key Responsibility statement: Design and develop scalable PySpark data pipelines to ensure efficient processing of large datasets, enabling faster insights and business decision-making. Leverage Databricks notebooks for collaborative data engineering and analytics, improving team productivity and reducing development cycle times. Write clean, modular, and reusable Python code to support data transformation and enrichment, ensuring maintainability and reducing technical debt. Implement data quality checks and validation logic within ETL workflows to ensure trusted data is delivered for downstream analytics and reporting. Optimize Spark jobs for performance and cost-efficiency by tuning partitions, caching strategies, and cluster configurations, resulting in reduced compute costs. Qualifications Your Skills & Experience: Solid understanding of Python programming fundamentals, especially in building modular, efficient, and testable code for data processing. Familiarity with libraries like pandas, NumPy, and SQLAlchemy (for lightweight transformations or metadata management). Proficient in writing and optimizing PySpark code for large-scale distributed data processing. Deep knowledge of Spark internals, partitioning, shuffling, lazy evaluation, and performance tuning. Comfortable using Databricks notebooks, clusters, and Delta Lake. Additional information Set Yourself Apart With: Familiarity with cloud-native services like AWS S3, EMR, Glue, Lambda, or Azure Data Factory. Experience deploying or integrating pipelines within a cloud environment adds flexibility and scalability. Experience with tools like Great Expectations or custom-built validation logic to ensure data trustworthiness. A Tip from the Hiring Manager: This person should be highly organized, adapt quickly to change, and thrive in a fast-paced organization. This is a job for the curious, make-things-happen kind of person. Someone who thinks like an entrepreneur and can motivate and move their team to achieve and drive impact. Benefits of Working Here: Gender-Neutral Policy 18 paid holidays throughout the year. Generous parental leave and new parent transition program Employee Assistance Programs to help you in wellness and well-being.