Big Data

Hiring location: United States This is a remote position. Design & Develop “Transformations” aspects using the ELT framework to modernize the Ingestion pipelines and build data transformations at scale ● Work closely with other data teams & Data Science teams and participate in the development of Ingestion pipelines ● Provide technical expertise in the areas of design and implementation of Ratings Data Ingestion pipelines with modern AWS cloud and other technologies such as S3, Hive, Databricks, Scala, Python, and Spark ● Build and maintain a data environment for speed, accuracy, consistency, and ‘up’ time ● Work closely with other data teams & Data Science teams and participate in the development of Ingestion pipelines ● Ensure data governance principles are adopted, data quality checks and data lineage implemented in each hop of the data ● Be in tune with emerging trends Big data and cloud technologies and participate in the evaluation of new technologies ● Ensure compliance through the adoption of enterprise standards and promotion of best practice / guiding principles aligned with organization standards What you'll bring: ● Should be in a position to handle issue resolution and provide direction to teams both technically and functionally ● Should be able to articulate and convert requirements into solutions. ● Experience With Machine Learning Libraries and Frameworks (TensorFlow, MLlib) is an added advantage ● Experience with development frameworks as well as data and integration technologies such as Informatica, Python, Scala ● Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally. ● Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management ● Excellent analytical thinking, interpersonal, oral, and written communication skills with a strong ability to influence both IT and business partners ● Ability to prioritize and manage work to critical project timelines in