Project

Our client is a healthcare analytics company that delivers real-world evidence for the manufacturers, and purchasers of medical treatments and technologies. This company analyzes data from the real world to produce transparent, rapid, and scientifically validated answers on safety, effectiveness, and value. Also, it informs health care's most critical decisions (what works best, for who, and when) to guide product development, commercialization, and payment innovation.

Role

Your primary responsibility will be developing transformation logic against disparate datasets in my client's Evidence Platform. You will work closely with our Product and Science team in developing custom transformation logic for longitudinal data, which is in Java / Python / Scala and/or R, and executed over a Spark cluster. In addition, you will be integral in developing and enhancing our platform and its connections to Spark and a combination of big data infrastructure.

Qualifications

• Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Information Systems, or a related field.
• 5+ years of experience or equivalent in the position offered or related position, including.
• 2 year of experience with: designing, developing, maintaining large-scale data ETL pipelines using Java/Scala in AWS, Hadoop, Spark, and DataBricks to manage Apache Spark infrastructure.
• Experience working with programming languages like Java, Python, SQL, and SCALA.
• Experience or knowledge of building and optimizing ETL pipelines
• Experience in data quality management, data validation and/or data governance
• Experience building systems with large data sets
• Experience or working knowledge with distributed systems
• Experience translating requirements from product, DevOps teams to technology solutions using SDLC.

What they offer

• Work-life Balance
• 25 vacation days
• Flexible start and end of working day
• Flexible in-office work commitment
• Sabbatical opportunity after five years of employment

Benefits

• Daily in-office lunch stipend and a fully stocked kitchen
• Comprehensive private health coverage w/ out-of-network reimbursement o