Senior Data Engineer (AWS + Databricks + Python)

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 We are looking for a Senior Data Engineer to design and build scalable data engineering solutions in AWS. This role combines solution architecture, hands-on development, and team leadership to deliver large-scale data transformation projects. You will work on production-grade systems involving batch and real-time pipelines, cloud-native services, and modern data platforms. Responsibilities Your Impact Design and implement scalable data architectures to build or migrate complex data pipelines in AWS. Build and maintain batch and real-time data pipelines using AWS managed services and modern data processing frameworks. Lead end-to-end delivery of large data transformation initiatives, including architecture, design, and implementation. Define and enforce data engineering best practices, standards, and governance across projects. Develop and optimize data models and database designs supporting analytical and operational use cases. Collaborate with cross-functional teams in agile environments to deliver data-driven product capabilities. Drive improvements in data quality, testing, monitoring, and platform tooling. Integrate external and third-party data sources via APIs into enterprise data ecosystems. Contribute hands-on to development while guiding and mentoring team members. Qualifications Skills & Experience 10+ years of experience building ETL/data pipelines processing large-scale datasets. 5+ years of experience with AWS services such as S3, Glue, Aurora, Step Functions (or equivalent cloud technologies). 2+ years of hands-on experience with Databricks. Strong experience in data modeling, database design, and data migration from legacy systems. Advanced SQL skills. Proficiency in at least one programming language: Python (preferred), Scala, Java, or Go. Experience working in large, distributed teams contributing to development and debugging. Strong communication skills with experience interacting with clients and stakeholders. Set Yourself Apart With Experience developing APIs for data integration and interoperability. Knowledge of in-memory databases such as Redis. AWS certifications in data engineering, cloud architecture, or related areas. Experience writing and maintaining infrastructure as code. Experience with CI/CD pipelines and automation tools (e.g., ADO pipelines). Exposure to performance optimization and scalability in distributed data systems. 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. 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 [email protected]

Skills & Experience 10+ years of experience building ETL/data pipelines processing large-scale datasets. 5+ years of experience with AWS services such as S3, Glue, Aurora, Step Functions (or equivalent cloud technologies). 2+ years of hands-on experience with Databricks. Strong experience in data modeling, database design, and data migration from legacy systems. Advanced SQL skills. Proficiency in at least one programming language: Python (preferred), Scala, Java, or Go. Experience working in large, distributed teams contributing to development and debugging. Strong communication skills with experience interacting with clients and stakeholders. Set Yourself Apart With Experience developing APIs for data integration and interoperability. Knowledge of in-memory databases such as Redis. AWS certifications in data engineering, cloud architecture, or related areas. Experience writing and maintaining infrastructure as code. Experience with CI/CD pipelines and automation tools (e.g., ADO pipelines). Exposure to performance optimization and scalability in distributed data systems.

Your Impact Design and implement scalable data architectures to build or migrate complex data pipelines in AWS. Build and maintain batch and real-time data pipelines using AWS managed services and modern data processing frameworks. Lead end-to-end delivery of large data transformation initiatives, including architecture, design, and implementation. Define and enforce data engineering best practices, standards, and governance across projects. Develop and optimize data models and database designs supporting analytical and operational use cases. Collaborate with cross-functional teams in agile environments to deliver data-driven product capabilities. Drive improvements in data quality, testing, monitoring, and platform tooling. Integrate external and third-party data sources via APIs into enterprise data ecosystems. Contribute hands-on to development while guiding and mentoring team members.