Manager Data Engineering DE - Big Data AWS
Publicis Sapient
Bengaluru, Karnataka, India
Job Description As Manager, Data Engineering, you will be responsible for translating client requirements into design, architecting, and implementing AWS Cloud-based big data solutions for clients. 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. 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 AWS 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. #LI-REMOTE 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 AWS 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 AWS Cloud. 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 AWS 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 of 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. Set Yourself Apart With: Certification on AWS cloud platform or big data technologies. Strong analytical and problem-solving skills. Excellent understanding of data technologies landscape / ecosystem. A Tip from the Hiring Manager: Join the team to sharpen your skills and expand your collaborative methods. Make an impact on our clients and their businesses directly through your work. Additional Information Gender Neutral Policy 18 paid holidays throughout the year Generous parental leave and new parent transition program Flexible work arrangements Employee Assistance Programs to help you in wellness and well being 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 the 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.
