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
Responsibilities
- Design and implement end-to-end data ingestion pipelines using Azure services, including API-based ingestion and Azure Data Factory (ADF).
- Build and manage lakehouse and data warehouse solutions using modern data storage formats to support analytical and operational workloads.
- Develop and optimize data transformations using PySpark, ensuring scalability, performance, and cost efficiency.
- Apply medallion architecture (bronze, silver, gold layers) to enable high-quality, governed, and reusable datasets.
- Partner with cross-functional teams to support data modeling, analytics, and downstream consumption use cases.
- Contribute to best practices around data quality, reliability, and maintainability across the data platform.
Qualifications
- Hands-on experience or strong working knowledge of Microsoft Fabric, including its role in modern analytics and lakehouse architectures.
- Proven experience working in Azure for data ingestion and orchestration.
- Strong experience with Azure Data Factory (ADF) for pipeline development and scheduling.
- Experience building API-based data ingestion solutions.
- Solid understanding of data storage formats, including CSV, JSON, and Parquet.
- Experience designing and working with data warehouses and lakehouse architectures.
- Strong foundation in data modeling concepts for analytical workloads.
- Practical experience implementing medallion architecture patterns.
- Proficiency in PySpark for large-scale data transformations and optimization.
- Ability to write clean, maintainable, and well-documented data pipelines.
Set Yourself Apart
- Experience optimizing Spark jobs for performance and cost in cloud environments.
- Familiarity with data governance, data quality, or observability practices in large-scale data platforms.
- Experience collaborating with analytics, data science, or AI teams on production-grade data solutions.
- Exposure to agile delivery models and working in cross-functional, client-facing teams.
Additional information
Additional Information
- An inclusive workplace that promotes diversity and collaboration.
- Access to ongoing learning and development opportunities.
- Competitive compensation and benefits package.
- Flexibility to support work-life balance.
- Comprehensive health benefits for you and your family.
- Generous paid leave and holidays.
- Wellness program and employee assistance.
Pay Range: $143,000 - $193,000
As part of our dedication to an inclusive and diverse workforce, Publicis Sapient is committed to Equal Employment Opportunity without regard for race, color, national origin, ethnicity, gender, protected veteran status, disability, sexual orientation, gender identity, or religion. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at hiring@publicis.sapient.com.
Your information will be kept confidential according to EEO guidelines.