Data Engineer

The Team

Our Health Engineering Solutions (HES) team works side by side with customers to articulate a vision for success, and then make it happen. We know success doesn't happen by accident. It takes the right team of people, working together on the right solutions for the customer. We are looking for a seasoned Data Engineer who will be a key driver to make this happen.

Our team supports the vision to improve patient quality care and consumer decision-making by hospital providers across the country, by collecting, computing, and publicly reporting outcomes-based hospital quality measure data. This contract will serve to develop a human-centric reporting system that allows refinement, filtering, and data comparison, as well as the ability to view supplemental information. Leveraging modern technologies, DevOps practices, and cloud-based infrastructure, our dynamic work environment involves multiple project teams collaborating toward a common vision of delivering an integrated solution.

The Work

We are looking for a talented Data Engineer who is eager to apply computer science, software engineering, databases, and distributed/parallel processing frameworks to prepare big data for the use of data analysts and data scientists. If you have experience with Apache Parquet, Apache Spark, AWS Glue, AWS Athena, Databricks and want your work to contribute to systems that collect healthcare data used by hundreds of thousands of daily users, we want to (virtually) meet you!

You will work on projects that support the Centers for Medicare and Medicaid Services (CMS) as we develop a next-generation analytics and reporting system that directly impacts healthcare quality. You will use Spark, Apache and other AWS technologies to build data processing pipelines that derive information from large sets of government data. This program allows for the continued quality of clinicians’ work according to CMS standards. We are a collaborative company, so we want you to use your knowledge of Spark to teach others, inform design decisions, and debug runtime problems.

Job Location: Remote; however, this position requires that the job be performed in the United States and there will be travel of approximately 10% to a customer site. If you accept this position, you should note that ICF does monitor employee work locations and blocks access from foreign locations/foreign IP addresses and prohibits personal VPN connections.

Tools & Technology

• Python
• PySpark
• Spark
• Databricks
• PostgreSQL
• Jenkins
• AWS Glue
• AWS Athena
• JAVA
• Git and GitHub
• Confluence

Key Responsibilities and Job Duties

• Design and build data processing pipelines using tools and frameworks in the AWS ecosystem. 
• Analyze requirements and architecture specifications to create a detailed design document. 
• Responsible for data engineering functions including data extract, transformation, loading, integration in support of modern cloud computing platforms like AWS. 
• Work with huge data sets and other Data Engineers and/or Scientists on analyzing this data using various algorithms. 
• Implement and configure big data technologies as well as tune processes for performance at scale. 
• Design and build ETL pipelines to automate the ingestion and data migration of structured and unstructured data. 
• Work with DevOps engineers on CI, CD, and IaC (Continuous Integration, Continuous Delivery, and Infrastructure as Code) processes; read specifications and translate them into code and design documents; and perform code reviews and develop processes for improving code quality. 
• Be proactive and constantly pay attention to the scalability, performance, and availability of our systems. 
• Responsible for deploying the developed solution in AWS environment and examine the results for accuracy. 
• Write complex unit and integration tests for all data processing code
• Perform code reviews and develop processes for improving code quality

Required Qualifications

• Bachelor’s degree required (degree in Computer Science or related field preferred)
• 5+ years of high-volume experience with Python, PySpark, the Spark Engine, and the Spark Dataset API
• 2+ years of experience with Agile methodology
• 2+ years of experience performing data pipeline and data validation
• Candidate must be able to obtain and maintain a Public Trust Clearance
• Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S.
• Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years

Preferred Qualific