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Senior Observability Engineer Jobs in Springfield, MA

Senior Software Architect

Hartford, CT · On-site

$130K - $177K/yr

You will partner closely with engineering leads, ML engineers, and product teams within CIE ... observability * Contribute to LLM-integrated system design including RAG pipelines, embedding ...

Lead Data Engineer

Holyoke, MA · On-site

$150K - $170K/yr

Experience with data governance, data quality frameworks, and observability tools This employer ... We will also consider a Mid to Senior level Data Engineer. The pay range for the Mid to Senior ...

AVP, Software Engineering Lead

Hartford, CT · On-site +1

$255K/yr

The AVP, Software Engineering Lead is a senior technology leader responsible for defining and ... Ensure production readiness through robust testing, observability, monitoring, and incident ...

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Senior Observability Engineer information

See Springfield, MA salary details

$59.3K

$126.1K

$182.9K

How much do senior observability engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for senior observability engineer in Springfield, MA is $126,114.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,100.00 and $143,000.00 per year, depending on experience, location, and employer.

What is a Senior Observability Engineer?

A Senior Observability Engineer is a seasoned IT professional responsible for designing, implementing, and maintaining systems that monitor and provide insights into the performance, health, and reliability of software applications and infrastructure. They utilize tools for logging, monitoring, tracing, and alerting to ensure that systems are observable and any issues can be quickly detected and resolved. In addition to technical expertise, they often collaborate with development and operations teams to establish best practices, improve incident response, and optimize system performance. Their work is crucial for maintaining uptime, enhancing customer experiences, and supporting the scalability of technology platforms.

How does a Senior Observability Engineer typically collaborate with development and operations teams?

A Senior Observability Engineer works closely with both development and operations teams to ensure robust monitoring, logging, and tracing solutions are in place across all applications and infrastructure. They often participate in architecture discussions to advise on best practices for instrumenting code and systems for observability. By analyzing metrics and alerting patterns, they help teams proactively resolve issues and optimize system performance. This role also involves mentoring engineers on observability tools and fostering a culture of transparency and accountability in incident response.

What is the difference between Senior Observability Engineer vs Site Reliability Engineer?

AspectSenior Observability EngineerSite Reliability Engineer
CredentialsExperience with monitoring tools, scripting, cloud platformsSame as Senior Observability Engineer, often with SRE certifications
Work EnvironmentFocus on monitoring, logging, and tracing systemsFocus on system reliability, automation, and incident response
Industry UsageUsed in tech companies emphasizing system observabilityCommon in large-scale tech and cloud services
Search/Comparison IntentOften compared for monitoring rolesCompared for reliability and system stability roles

While both roles require expertise in cloud platforms and scripting, the Senior Observability Engineer primarily focuses on designing and maintaining monitoring, logging, and tracing systems to ensure system visibility. In contrast, a Site Reliability Engineer emphasizes system reliability, automation, and incident management to maintain service uptime. Both roles are vital in tech environments but serve different core functions related to system health and stability.

What are the key skills and qualifications needed to thrive as a Senior Observability Engineer, and why are they important?

To thrive as a Senior Observability Engineer, you need expertise in monitoring, logging, and tracing systems, with a solid background in computer science or a related field. Familiarity with tools like Prometheus, Grafana, ELK stack, and cloud platforms, as well as certifications such as AWS Certified DevOps Engineer, are typically required. Strong problem-solving, collaboration, and communication skills are critical for effectively diagnosing and resolving complex infrastructure issues. These skills ensure reliable system performance, rapid incident response, and continuous improvement of the technology environment.
What are the most commonly searched types of Observability Engineer jobs in Springfield, MA? The most popular types of Observability Engineer jobs in Springfield, MA are:
What are popular job titles related to Senior Observability Engineer jobs in Springfield, MA? For Senior Observability Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Senior Observability Engineer jobs in Springfield, MA look for? The top searched job categories for Senior Observability Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Senior Observability Engineer jobs? Cities near Springfield, MA with the most Senior Observability Engineer job openings:
Infographic showing various Senior Observability Engineer job openings in Springfield, MA as of June 2026, with employment types broken down into 41% Full Time, 54% Part Time, and 5% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $126,114 per year, or $60.6 per hour.
Cyber AI Data Engineer Senior Consultant

Cyber AI Data Engineer Senior Consultant

Deloitte

Hartford, CT • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Deloitte rating

8.0

Company rating: 8.0 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

71st of 146 rated financial services


Job description

Job Summary:
Deloitte is looking for a hands-on Data Engineer to build and operate the governed data foundations powering cyber risk and AI-enabled cyber workflows. The role involves designing production-grade pipelines and services, implementing data quality checks, and partnering with stakeholders to translate requirements into implementable controls.
Responsibilities:
• Building scalable batch and stream processing pipelines that ingest security telemetry, control evidence, and compliance artifacts into governed data stores.
• Designing data models for risk and controls domains, including key risk indicators, issues and defects, risk acceptance, control testing outcomes, audit evidence, and policy exceptions, and enabling self-service analytics and dashboards.
• Implementing data quality checks, lineage, metadata, and access controls to support auditability, regulatory defensibility, and repeatable evidence generation.
• Developing AI-enabled capabilities that accelerate governance, risk, and compliance and cyber operations, including evidence summarization, control testing assist, policy question-and-answer, investigation copilots, ticket triage, and exception reasoning using agentic patterns, workflow orchestration, and retrieval-augmented generation.
• Engineering integrations between data platforms, governance, risk, and compliance workflows, and enterprise systems using application programming interfaces, event patterns, and connectors, with observability and runbooks for production support.
• Partnering with Cyber, Risk, Compliance, Privacy, and Legal stakeholders to translate requirements into implementable controls and developer-ready guardrails.
Qualifications:
Required:
• Bachelor's degree or equivalent practical experience.
• 4+ years of experience in data engineering and software development using Python and SQL.
• Experience building production data pipelines and data models for batch processing, stream processing, or both, and deploying solutions using cloud platforms, containers, infrastructure as code, application programming interfaces, and secrets management.
• Experience implementing data governance controls including data classification, personally identifiable information handling, least-privilege access, encryption, secrets management, retention, audit logging, and lineage or metadata management.
• Experience supporting governance, risk, and compliance workflows, including risk reporting, audit data requests, controls monitoring, controls testing, compliance metrics, governance, risk, and compliance tool integrations, and large language model-enabled applications using retrieval-augmented generation, vector or hybrid retrieval, tool or function calling, evaluation or monitoring, prompt-injection defenses, and secure access patterns.
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Experience in consulting or a Big 4 environment.
• Experience with Java, Go, or JavaScript.
• Experience integrating with ServiceNow GRC, Archer, OneTrust, or BigID and building evidence pipelines mapped to control objectives.
• Experience building pipelines for security information and event management, security orchestration, automation, and response, vulnerability, identity, or cloud security posture data.
• Experience operationalizing large language model operations or machine learning operations capabilities, including evaluation, monitoring, versioning, and governance workflows.
• Security certification such as CompTIA Security+, Certified Information Security Manager, Certified Information Systems Auditor, Certified Information Systems Security Professional, or a cloud certification.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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