Lead Data Engineer

What you need to know about the role- We are hiring talented and creative Feature engineer for AIML platform team based in Chennai, you will be customer-centric, strategic & analytical in decision making and laser-focused on executing at scale. You thrive on the challenge of building and optimizing platforms at scale, are deeply passionate about leveraging cutting-edge technologies, and are dedicated to innovation and market success. You will have a chance to work on solving real world problems and gain practical experience in end-to-end Feature building & Machine Learning life cycle. You will design, build, and optimize the platform for Feature Engineering to support ML pipeline and data infrastructure. Additionally, you will gain domain expertise in a variety of industries, working with data scientists, researchers, and engineers to build Features required for ML models used across all PayPal domains. Meet our team PayPal RAMPS(Risk & AI/ML Platforms Solutions) is responsible for building the Features Engineering & ML capabilities to help data scientists and data analysts with the end-to-end feature development lifecycle. We build state of the art and innovative feature & ML infrastructure to support key product functions such as Global Analytics Data science, Fraud risk, Credit risk, Compliance, Personalization, Recommendations, Customer success, and other domains across PayPal.

Your way to impact:

• Strong critical thinking and problem-solving skills with the ability to address complex technical and non-technical challenges. 
• Ability to influence and strong communication to interact with at all levels of the organization and across multiple domains.
• Ability to solve technical problems and data science discussions and engagements that involve multiple personas including data scientists, data engineers, analysts and developers. 

Your day to day:

• Design and develop highly scalable and efficient Feature Engineering platform that enables data scientists to build, deploy, and monitor Features and machine learning solutions end-to-end.  
• Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices.  
• Drive innovation by researching and incorporating state-of-the-art Feature Engineering & Machine learning techniques, tools, and frameworks into the Feature Engineering platform.  
• Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner.
• Work as a team player and foster a culture of collaboration, innovation, and continuous learning.  
• Explore state-of-the-art deep learning techniques and Partner with data science and domain engineering teams to support the business transformation through AI.

• Develop trusted partnership with business, product, data scientists and architecture leaders to drive optimized platform product delivery

What do you need to bring:

• Minimum of 10 years of relevant experience in key technologies mention below.
• Good track record of over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; proven results in delivery on platform products.   
• Masters / bachelor’s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technical expertise in one or more of the above-mentioned areas or equivalent practical experience.  
• Strong proficiency in SQL, Hadoop, Spark, Google cloud platform (Big Query, Google cloud storage & Data proc), and Data Engineering techniques, with hands-on experience in developing and deploying large scale Feature data marts/store.  
• Expertise in anyone/ more programming languages such as Python, Go, Java, and proficiency in machine learning techniques.
• Experience working in large scale Feature engineering infrastructure or MLOps platforms and Bigdata platforms technologies such as Hadoop, BigQuery, Spark, Hive and HDFS.
• Experience with Jupyter Notebook, Kubeflow, Airflow, Uc4 Scheduling, Argo, GPU and HPC
• Stay up to date with the latest advancements in AI/ML technology and industry trends and leverage this knowledge to enhance the platform's capabilities.  
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). 
• Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner  
• Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential. 

**We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.