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Entry Level Observability Engineer Jobs in Washington, DC

Data Engineer I

Washington, DC · On-site +1

$85K/yr

About the Role We're hiring an entry-level Data Engineer to join our Data Engineering team. You'll ... Experience with data testing/observability tools and lineage documentation. * Experience designing ...

Jr. Front End Developer

Vienna, VA · On-site

$104K - $121K/yr

Experience with monitoring, logging, and observability tools * Exposure to DevSecOps practices and ... From entry-level employees to senior leaders, we believe theres always room to learn. We offer ...

Jr. Front End Developer

Vienna, VA · On-site

$104K - $121K/yr

Experience with monitoring, logging, and observability tools * Exposure to DevSecOps practices and ... From entry-level employees to senior leaders, we believe there's always room to learn. We offer ...

Entry Level Observability Engineer information

See Washington, DC salary details

$34K

$78.6K

$133.6K

How much do entry level observability engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for entry level observability engineer in Washington, DC is $78,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,300.00 and $88,900.00 per year, depending on experience, location, and employer.

What are some common challenges faced by entry level observability engineers, and how can they overcome them?

Entry level observability engineers often encounter challenges such as learning a variety of monitoring tools, understanding complex system architectures, and troubleshooting issues across distributed environments. It can be overwhelming to quickly grasp the different metrics, logs, and traces involved in modern infrastructure. To overcome these challenges, it's helpful to proactively seek mentorship from experienced team members, participate in hands-on projects, and leverage online resources or company training programs. Developing a strong foundation in scripting and automation can also make it easier to handle recurring monitoring tasks and respond effectively to incidents.

What does an Entry Level Observability Engineer do?

An Entry Level Observability Engineer is responsible for helping monitor, analyze, and improve the performance and reliability of software systems. They typically work with tools that collect metrics, logs, and traces to provide insights into system health and detect issues early. Their duties may include setting up monitoring dashboards, configuring alerts, assisting with incident response, and collaborating with development and operations teams to ensure systems are observable and performant. This role is ideal for those starting a career in DevOps or site reliability engineering, as it provides hands-on experience with industry-standard tools and practices.

What is the difference between Entry Level Observability Engineer vs Junior DevOps Engineer?

AspectEntry Level Observability EngineerJunior DevOps Engineer
Required CredentialsBachelor's in CS or related field, basic knowledge of monitoring toolsBachelor's in CS or related field, basic scripting skills
Work EnvironmentFocus on monitoring, logging, and observability tools within IT/tech teamsInvolved in deployment, automation, and infrastructure management
Employer & Industry UsageTech companies, SaaS providers, cloud servicesTech firms, startups, cloud service providers
Common Search & Comparison IntentUnderstanding entry-level roles in observabilityExploring roles related to DevOps and infrastructure

Entry Level Observability Engineers primarily focus on monitoring, logging, and ensuring system reliability, while Junior DevOps Engineers handle deployment, automation, and infrastructure tasks. Both roles often require similar educational backgrounds but differ in daily responsibilities and focus areas within tech environments.

What are the key skills and qualifications needed to thrive as an Entry Level Observability Engineer, and why are they important?

To thrive as an Entry Level Observability Engineer, you need a solid understanding of IT infrastructure, basic programming or scripting skills, and foundational knowledge of monitoring concepts, often supported by a degree in computer science or a related field. Familiarity with observability tools like Prometheus, Grafana, Datadog, or Splunk, as well as basic cloud platform usage, is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret data and collaborate with technical teams. These skills are essential for maintaining system reliability and quickly identifying and resolving issues in modern IT environments.
What are the most commonly searched types of Observability Engineer jobs in Washington, DC? The most popular types of Observability Engineer jobs in Washington, DC are:
What are popular job titles related to Entry Level Observability Engineer jobs in Washington, DC? For Entry Level Observability Engineer jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Entry Level Observability Engineer jobs in Washington, DC look for? The top searched job categories for Entry Level Observability Engineer jobs in Washington, DC are:

Data Engineer I

Inroads

Washington, DC • On-site, Remote

$85K/yr

Full-time

Medical, Retirement, PTO

Posted 8 days ago


Job description

About Inroads:

Inroads applies data, analytics, technology, research, and content development to co-create services and programs that are personalized, relevant, and engaging for the communities who rely on them. Our deep understanding of digital services, policy implementation, and how communities consume information allows us to seamlessly integrate with organizations and public-sector teams to revolutionize how they deliver complex services at scale.

About the Role

We’re hiring an entry-level Data Engineer to join our Data Engineering team. You’ll take ownership of building reliable ELT/ETL pipelines and strong analytical data models using dbt. You don’t need to know everything on day one, but you must be eager to learn, experiment, and grow quickly.

In this position, you will:

  • Build, test, and document dbt models (staging, intermediate, marts) aligned to Kimball dimensional modeling best practices.
  • Implement data quality checks (dbt tests, sources, freshness) and contribute to monitoring data reliability.
  • Collaborate with analytics, product, and domain stakeholders to translate business needs into well-modeled datasets.
  • Proactively audit, define, and standardize key business metrics in collaboration with stakeholders to ensure consistency and trust across reporting platforms.
  • Support source onboarding and ingestion from APIs, files, or databases into the warehouse.
  • Maintain clear documentation for datasets, lineage, and transformation logic.
  • Assist with CI/CD for analytics code (Git workflows, PR reviews, environments).
  • Optimize model performance (incremental strategies, partitions/clustering, query tuning).
  • Troubleshoot pipeline/data issues and contribute to root-cause analyses.
  • Proactively identify improvement opportunities and drive them to completion with high ownership.

What we are seeking:

  • 2 years of experience in data engineering, analytics engineering, or related field (internships, coursework, and projects encouraged) OR an undergraduate degree or higher in a related field
  • Proficiency in SQL; able to write clean, performant queries.
  • Practical experience with dbt (models, tests, documentation, sources; familiarity with Jinja/macros is a plus).
  • Solid grasp of Kimball dimensional modeling (star/snowflake schemas, facts and dimensions, SCDs).
  • Demonstrated ability to translate complex business logic into efficient, technical data structures.
  • Understanding of data warehousing and ELT/ETL patterns.
  • Familiarity with Git and collaborative development workflows.
  • Strong problem-solving and communication skills; attention to detail.
  • Demonstrated willingness to learn quickly and take ownership of outcomes.

Additional experience to stand out:

  • Workflow orchestration experience (Airflow, Dagster, Prefect).
  • Cloud data warehouse exposure (Snowflake preferred).
  • Basic Python skills for data tasks (ETL scripts, API integrations).
  • Experience with data testing/observability tools and lineage documentation.
  • Experience designing and implementing data models specifically for consumption by internal technical teams (Data Analysts, Data Scientists).
  • Exposure to CI/CD for analytics (dbt Cloud/Jobs, GitHub Actions).
  • Domain knowledge of the U.S. healthcare insurance marketplace (Healthcare.gov) data and metrics.

What We Offer:

Inroads offers a friendly work environment and competitive compensation and benefits package including:

  • Salary: $85,000
  • Premier health insurance plan
  • 401K matching
  • Unlimited vacation leave
  • Paid sick, personal, and volunteer leave
  • 13 paid holidays
  • 15 weeks paid parental leave
  • Professional development stipend & tuition reimbursement
  • Employee Assistance Program (EAP)
  • Supportive & collaborative culture 
  • Flexible working hours
  • Remote friendly (within the U.S.)
  • And more! 

The salary range for candidates who meet the minimum posted qualifications reflects the Company’s good faith understanding and belief as to the wage range, and is accurate as of the date of this job posting.

At Inroads, we celebrate, support and thrive on differences. Not only do they benefit our services, products, and community, but most importantly, they are to the benefit of our team. Qualified people of all races, ethnicities, ages, sex, genders, sexual orientations, national origins, gender identities, marital status, religions, veterans statuses, disabilities and any other protected classes are strongly encouraged to apply. Inroads endeavors to make reasonable accommodations for qualified applicants with a disability unless the accommodation would impose an undue hardship on the operation of our business. If an applicant believes they require such assistance to complete the application or to participate in an interview, or has any questions or concerns, they should contact the Senior Director, People Operations.  Inroads participates in E-verify. EEO is the Law.

Collection of Personal Information Notice:

As you are likely aware, by submitting your job application, you are submitting personal information to our company. We collect various categories of personal information, including identifiers, protected classifications, professional or employment related information and sensitive personal information. We may retain and use this information for up to three years, in order to come to a decision on whether or not you are a good fit for our company. We may also retain or use some of this information to comply with any requirements under law, or for purposes of defending ourselves in any litigation. We do not use this information for any other purpose, or share it with third parties, unless you become an employee. To learn more, or to see our full Notice to Job Applicants, please click here.