Job description

What you'll do: - Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. - Review project objectives and determine the best technology for implementation. Implement best practice standards for development, build and deployment automation. - Run daily operations of the data infrastructure and support other engineers and analysts on data investigations and operations. - Monitor and report on all data pipeline tasks while working with appropriate teams to take corrective action quickly, in case of any issues. - Work with internal teams to understand current process and areas for efficiency gains - Write well-abstracted, reusable, and efficient code. - Participate in the training and/or mentoring programs as assigned or required. - Adheres to the Quest Analytics Values and supports a positive company’s culture. - Responds to the needs and requests of clients and Quest Analytics management and staff in a professional and expedient manner. What it requires: - Bachelor's degree in computer science or related field. - 3 years of work experience with ETL, data operations and troubleshooting, preferably in healthcare data. - Proficiency with Azure ecosystems, specifically in Azure Data Factory and ADLS. - Strong proficiency in Python for scripting, automation, and data processing. - Advanced SQL skills for query optimization and data manipulation. - Experience with distributed data pipeline tools like Apache Spark, Databricks, etc. - Working knowledge of database modeling (schema design, and data governance best practices.) - Working knowledge of libraries like Pandas, numpy, etc. - Self-motivated and able to work in a fast paced, deadline-oriented environment - Excellent troubleshooting, listening, and problem-solving skills. - Proven ability to solve complex issues. - Customer focused.

Requirements