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Analytics Engineer Jobs in Washington, DC (NOW HIRING)

Gigatec Engineering

Data Analytics Engineer

Annapolis, MD · On-site

$113K - $136K/yr

... Engineering role, you'll get to build the workflow engines behind the curtain, designing reliable Apache Airflow pipelines that keep data moving cleanly, efficiently, and on schedule for analytics ...

SES

Data Analytics Engineer - ZL

Washington, DC · On-site

$129K - $155K/yr

Financial Services Domain Knowledge Seeking an experienced Data Analytics Engineer / Business UAT Tester with 7+ years of analytics, monitoring, visualization, production support, and developer ...

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All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Washington, DC

Analytics Engineer information

See Washington, DC salary details

$67.1K

$117.2K

$191.1K

How much do analytics engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for analytics engineer in Washington, DC is $117,175.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,503.00 and $131,523.00 per year, depending on experience, location, and employer.

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

What are the key skills and qualifications needed to thrive as an analytics engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in Washington, DC? The most popular types of Analytics Engineer jobs in Washington, DC are:
What are popular job titles related to Analytics Engineer jobs in Washington, DC? For Analytics Engineer jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Analytics Engineer jobs in Washington, DC look for? The top searched job categories for Analytics Engineer jobs in Washington, DC are:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Washington, DC as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $117,175 per year, or $56.3 per hour.

Data Analytics Engineer

GIGATEC Engineering

Annapolis Junction, MD • On-site

$117K - $140K/yr

Full-time

Medical, Retirement

Re-posted 7 days ago

Job description

Perks and Benefits

  • 100% Paid Healthcare
  • 10% 401k in every paycheck
  • 100% Fully Vested!

NOTE – Our positions require a Top Secret clearance, as well as the favorable completion of a polygraph. Applicants must be authorized to work in the U.S. We are unable to sponsor an employment Visa.


What You’ll Be Doing (We don’t love the bullet points, but we love the work!)

In this key Data Engineering role, you'll get to build the workflow engines behind the curtain, designing reliable Apache Airflow pipelines that keep data moving cleanly, efficiently, and on schedule for analytics and operational needs.Required Skills
  • Experience using the Linux CLI and Linux tools
  • Experience developing Bash scripts to automate manual processes
  • Recent software development experience using Python and Java
  • Experience using Apache Airflow (DAG design, scheduling, operators, sensors) to orchestrate, schedule, and monitor complex workflows
  • Experience using Distributed Big Data processing engines including Apache Spark
  • Experience with containerization technologies such as Docker, containerd, and Podman
  • Experience with Git Source Control System

Desired Skills
  • Experience using the Atlassian Tool Suite (JIRA, Confluence)
  • Familiar with AWS Cloud Services and Infrastructure
  • Appreciates a sense of humor and the occasional well-timed joke. 😄

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