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General Dynamics Information Technology

Data Engineer Senior, Analytics Pipeline (FWA)

Posted 6 Hours Ago
Remote
Hiring Remotely in United States
111K-150K Annually
Senior level
Remote
Hiring Remotely in United States
111K-150K Annually
Senior level
Build and operate event-driven data pipelines processing healthcare claims data for fraud, waste, and abuse detection. Operationalize validated fraud signals, maintain alert delivery and partner dashboards, monitor pipeline reliability, and collaborate with data architects, scientists, and investigative teams. The role requires production-scale pipeline engineering using AWS, Snowflake, Python, and SQL in a fully remote environment.
The summary above was generated by AI

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

None

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

Analytics, Big Data Engineering, Data Management

Certifications:

None

Experience:

4 + years of related experience

US Citizenship Required:

No

Job Description:

DATA ENGINEER SENIOR
Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As a Data Engineer Senior at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward.

This role exists to turn new Partner data, as it lands in a multi-billion-record, multi-payer healthcare claims warehouse (the HFPP Trusted Third Party), into fraud, waste, and abuse (FWA) alerts and insights for Partners. You'll build and run the event-driven pipeline itself, from ingestion through signal integration, monitoring, and the alert and dashboard delivery that gets results in front of Partners.  You'll report through the program's analytic leadership and work with other teams in lockstep towards these goals.
Key Responsibilities

  • Build and operate the event-driven pipeline that picks up new Partner data as it lands in the HFPP warehouse and routes it into whatever fraud signals are currently deployed.

  • Take each newly-approved fraud signal and get it running in production: translate what Data Science already validated into pipeline logic that executes reliably at claims-record scale, without changing what the signal actually does.

  • Build and maintain the alert delivery layer; partner email notifications and the per-partner HTML dashboards in the HFPP Portal's analytics extension.

  • Watch the pipeline day to day. Latency, failed jobs, data that didn't land when it should have. Fix it before it costs a Partner an alert cycle, not after.

  • Build alongside the Data Architect and work collaboratively with the program’s technical and investigative teams.

  • Coordinate with Data Scientists on signal handoff without owning the methodology yourself.

Required Qualifications

  • Bachelor's degree in computer science, engineering, or a related field, or equivalent hands-on experience.

  • 4+ years building and operating production data pipelines, including at least one event-driven or streaming system running at real scale.

  • Hands-on experience with AWS and Snowflake, enough to build an event-driven ingestion pattern that reliably feeds a warehouse-native scoring layer.

  • Strong Python and SQL for pipeline and integration code, not just querying.

  • Experience building alerting or notification systems tied to a dashboard or portal a non-technical audience actually looks at.

  • Experience taking someone else's validated logic (a model, a rule set, a signal) and operationalizing it in production without changing what it does.

  • Comfortable working independently in a fully remote environment, building to someone else's architecture rather than setting your own.

Preferred Qualifications

  • Working familiarity with healthcare claims data or healthcare coding systems (ICD-10, CPT, HCPCS, DRG) 

  • Experience with pipeline monitoring/observability tooling and on-call-style incident response for a production data system.

  • Experience in a fraud, anomaly-detection, or other alerting pipeline specifically.

  • AWS certification (e.g., Solutions Architect Associate) or equivalent demonstrated depth.

GDIT IS YOUR PLACE
At GDIT, the mission is our purpose, and our people are at the center of everything we do.
● Growth: AI-powered career tool that identifies career steps and learning opportunities
● Support: An internal mobility team focused on helping you achieve your career goals
● Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
● Flexibility: Full-flex work week to own your priorities at work and at home
● Community: Award-winning culture of innovation and a military-friendly workplace
OWN YOUR OPPORTUNITY
Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

The likely salary range for this position is $110,500 - $149,500. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

Less than 10%

Telecommuting Options:

Remote

Work Location:

Any Location / Remote

Additional Work Locations:

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

 



Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at

gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

General Dynamics Information Technology Colorado Springs, Colorado, USA Office

Colorado Springs, United States, 0

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