Senior Elastic Engineer at Freddie Mac
McLean, VA 22102, USA -
Full Time


Start Date

Immediate

Expiry Date

11 Sep, 25

Salary

184000.0

Posted On

12 Jun, 25

Experience

7 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Languages, Data Architecture, Working Experience, Computer Science, Docker, Java, Scalability, Azure, Information Technology, Automation Tools, Aws, Scripting, Automation

Industry

Information Technology/IT

Description

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

POSITION OVERVIEW:

The Engineering Senior will be an active part of a team of about 10 Elastic Engineers providing observability services to the customers across the organization. Elastic is used for several specific cases with varying degrees of criticality. They will bring both technical expertise and coaching to junior members on the team.

QUALIFICATIONS:

  • Bachelor’s degree in computer science, Information Technology, or related field (or equivalent experience)
  • 5 – 7 years of hands-on experience with Elastic is highly desired.
  • Strong proficiency in scripting and programming languages (e.g., Python, NodeJS, Java, etc.)
  • Familiarity with logging and monitoring tools integrated with Elastic
  • Strong expertise in system design, data architecture, automation and scalability
  • Hands-on experience with DevOps practices, CI/CD pipelines, and infrastructure automation tools
  • Working experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes)
Responsibilities

KEY RESPONSIBILITIES:

  • Design and implement Elastic solutions for data ingestion, storage, application performance management, dashboards, Kibana, anomaly detection, Gen AI and analytics, ensuring high performance and scalability
  • Optimize Elastic stack components, including Elasticsearch, Logstash, Kibana, agents, etc.
  • Monitor and troubleshoot Elastic stack performance, addressing any bottlenecks or issues
  • Develop automated solutions for maintaining the Elastic cluster while following best practices for development, deployment, and monitoring
  • Stay updated on industry trends and advancements in the enterprise logging and monitoring space

KEYS TO SUCCESS IN THIS ROLE:

  • Coordinating the team for maximum efficiency
  • Serving as the initial technical contact for internal users and helping other junior team members to grow and succeed
  • Ability to build trust with coworkers and customers
  • Ability to display transparency is a must
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