1 hour ago
Reston, VA, USASenior
Base Salary
$175k - $184k/yr
Responsibilities
- Build data processing pipelines with Spark and Scala to derive information from large government datasets for CMS clinician scoring.
- Develop, modify, run, and test Spark applications using Scala APIs and Spark SQL.
- Process and aggregate data stored in Postgres, Redshift, and S3 Parquet files.
- Develop ETL routines, data engineering pipelines, data structures, and data models.
- Collaborate with UI, UX, quality analysis, DevOps, client, and other stakeholders on data and reporting requirements.
- Write unit and integration tests for data processing code.
- Work with DevOps engineers on CI, CD, and IaC.
- Perform code reviews and improve software code quality.
Requirements
- Bachelor’s degree or foreign equivalent in Computer Science, Information Technology, Software Engineering, or a related technical field plus five years of progressively responsible high-volume software development experience, or a master’s degree or foreign equivalent plus three years of relevant high-volume experience.
- At least three years of experience with Scala, Spark, the Spark Engine, and the Spark Dataset API.
- At least three years of SQL development, SQL analytics, and SQL tuning experience.
- At least two years of experience with AWS services including EMR, Redshift, CodeBuild, Lambda, and ECS.
- At least two years of experience with Git, GitHub, and Confluence/Jira.
- Prior Medicare or Medicaid data experience is preferred or required as an experience area.
- Federal Government contracting experience is required as an experience area.
- Must be able to obtain Public Trust clearance.
- Must have lived in the United States for three of the last five years.
- Any suitable combination of education, training, and experience will be accepted.
Benefits
- 100% remote work from anywhere within the United States.
- Position is eligible for the Employee Referral Bonus Program.
- The position is located under Nationwide Remote Office (US99), with work required to be performed in the United States.
Tech Stack
Categories
Data Engineering
