**Company description** **Manager, Data Engineering** **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 s businesses through designing the products and services their customers truly value. **Overview** As a Manager, Data Engineering at Publicis Sapient, you will guide clients through complex data challenges, architecting and implementing innovative solutions that drive digital transformation. Your role will be focused on delivering high-quality solutions by independently driving design discussions related to Data Ingestion, Transformation & Consumption, Data Storage and Computation Frameworks, Performance Optimizations, Infrastructure, Automation & Cloud Computing, and Data Governance & Security. The role requires a hands-on technologist with expertise in Big Data solution architecture and with a strong programming background in Java / Scala / Python. You will work closely with clients across industries, helping them navigate their digital transformation journeys by delivering scalable, high-quality data solutions. **Responsibilities** **Your Impact:** + Provide technical leadership and hands-on implementation role in the areas of data engineering including data ingestion, data access, modeling, data processing, visualization, design, and implementation. + Lead a team to deliver high quality big data technologies-based solutions on Azure Cloud. Manage functional & nonfunctional scope and quality. + Help establish standard data practices like governance and address other non-functional issues like data security, privacy, and quality. + Manage and provide technical leadership to a data program implementation based on the requirement using agile technologies. + Participate in workshops with clients and align client stakeholders to optimal solutions. + Consulting, Soft Skills, Thought Leadership, Mentorship etc. + People management, contributing to hiring and capability building. **Qualifications** **Your Skills & Experience:** + Overall 8+ years of IT experience with 3+ years in Data related technologies, and expertise of 1+ years in data-related Azure Cloud services and delivered at least 1 project as an architect. + Mandatory to have knowledge of Big Data Architecture Patterns and experience in the delivery of end-to-end Big Data solutions on Cloud (Azure/AWS/GCP) + Expert in programming languages like Java/ Scala and good to have Python + Expert in at least one distributed data processing framework: Spark (Core, Streaming, SQL), Storm or Flink, etc. + Expert in Hadoop eco-system with Azure cloud distribution and worked at least on one or more big data ingestion tools (Sqoop, Flume, NiFI, etc), distributed messaging and ingestion frameworks (Kafka, Pulsar, Pub/Sub, etc) and good to know traditional tools like Informatica, Talend, etc + Should have worked on any NoSQL solutions like Mongo DB, Cassandra, HBase, etc, or Cloud-based NoSQL offerings like DynamoDB, Big Table, etc. + Good Exposure in development with CI / CD pipelines. Knowledge of containerization, orchestration, and Kubernetes engine would be an added advantage. + Experience with Informatica (nice to have). + Basic knowledge of Gen AI (good to have). **Additional information** **Set Yourself Apart With:** + Certification on GCP/AWS any cloud platform or big data technologies. + Strong analytical and problem-solving skills. + Excellent understanding of data technologies landscape/ecosystem + Experience or exposure to ML/AI engineering + Experience with containerization and associated microservice tooling such as Docker, and Kubernetes. + Knowledge of data security (authentication, authorization, encryption for data at rest and in transit). + Understanding of monitoring and alerting tools for data environments. + Exposure to data governance, cataloging, and lineage tools. + Cloud or data technology certifications. + Active participation in the Data Engineering community (blogs, keynotes, POCs, hackathons). + Experience or exposure to working with Software or Platform engineering teams + A Bachelor s or Master’s degree in Computer Engineering, Computer Science, or a related field.