Skills and Qualifications

Master's degree in Business Analytics, Mathematics, Statistics, Data Science, Mechanical Engineering, Computer Applications, a related field, or a foreign equivalent plus 2 years of postbaccalaureate experience in job offered or related role. In Lieu of a Master's degree and 2 years of experience, Employer is willing to accept a Bachelor's degree in Business Analytics, Mathematics, Statistics, Data Science, Mechanical Engineering, Computer Applications, a related field, or a foreign equivalent plus 5 years of progressively responsible post-baccalaureate experience in job offered or related role. Applicants must have 2 years of experience (5 years in possession of a relevant Bachelor's degree) in the following: (1) utilizing Apache Spark (EMR) for distributed data processing at a large scale (PySpark); (2) running interactive SQL queries(Spark SQL); (3) Extracting and analyzing data from databases using SQL queries to find relevant insights and customer-specific aggregated results; (4) building ETL pipelines to collect, process, and integrate structured and semi-structured data from various data producers into Snowflake; (5) AWS Glue/Lambad to populate Data Catalog with metatable definitions and run scalable serverless data processing jobs as a part of ETL operations; (6) creating data and dimensional models, design Entity Relationships, and building scalable data pipelines to build Enterprise Data Warehouse; (7) utilizing AWS as an infrastructure service (IAAS) to build frameworks for data ingestion, transformation, and orchestration of data pipelines; and (8) building data pipelines DAG's, schedules, operators, connections, and hooks for data orchestration and optimize data workflows using Apache Airflow.

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