Sr. Software Engineer (Data Solutions), IS&T Ai & Data Platforms

requirements and workflows, and propose new features and ecosystem changes to streamline their experience of using the solutions on our platform. This is a hard-core software engineering role. A large part of an engineer's time is spent in writing code and designing/developing applications on cloud, with the remainder being spent on tuning and debugging codebase, supporting production applications and supporting our application end users. This role requires in-depth knowledge of innovative technologies and cloud data platform with the ability to independently learn new technologies and contribute to the success of various initiatives. We are looking for a hardworking and passionate person to join this amazing team. If you feel this is you, we'd love to hear from you. 7 or more years of experience developing enterprise level applications Implementation experience on Cloud with databases like SnowFlake, Big Query or Cloudera Programming experience with Python, Scala or Java. Experience in developing with SQL Bachelors degree or equivalent experience Strong hands-on experience in designing and development of cloud-based applications that include large scale compute services, database services, APIs to design RESTful services, ETL, queues and notification services. Experience in Enterprise-ready Cloud Data-Warehousing platforms like Snowflake is highly valued Hands-on knowledge of Spark cluster-computing framework & Kubernetes or similar containerization technologies. Experience developing Big Data applications using Java, Spark, Kafka is a huge plus Understanding of fundamentals of object-oriented design, data structures, algorithm design, and problem solving Cloud technology experience on platforms like AWS, Microsoft Azure, Google Cloud Data Visualization Tools: Proficient in data visualization, with experience in software such as Streamlit, Superset, Tableau, Business Objects, and Looker Data Insights and KPIs: Working experience on generating and visualizing data insights, metrics, and KPIs. Usage of basic ML models in the space of anomaly detection, forecasting, GenAI