Senior Elastic Engineer

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. Continue your career journey where your work contributes to a greater purpose.

The Engineering Senior (Elastic) will be an active part of a team of about 9 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.

The Elastic team works on logging and monitoring for any operational based needs across the organization. Their work directly impacts the health and operational effectiveness of most Freddie Mac systems. They are seen as technical authorities and trusted advisors to a broad range of customers.

You will drive and contribute to the development, optimization, and maintenance of our Elastic stack solutions. As the Engineering Senior (Elastic), you will implement technical solutions and collaborate across departments to ensure our systems are robust, scalable, and innovative.

• 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

• Bachelor’s degree in computer science, Information Technology, or related field (or equivalent experience)
• 5 – 7 years of hands‑on experience with Elastic
• Strong expertise in system design, data architecture, automation and scalability
• Strong knowledge of Machine learning concepts and hands‑on experience implementing Anomaly Detection ML jobs in Elastic
• Strong proficiency in scripting and programming languages (e.g., Python, NodeJS, Java, etc.)
• Hands‑on experience with Dev Ops practices, CI/CD pipelines, and infrastructure automation tools.
• Working experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).
• Familiarity with logging and monitoring tools integrated with Elastic.
• Experience using Gen AI tools for code development

• 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

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Please contact us to request accommodation.

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market‑leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $122,000 - $184,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.