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Analytics Engineer Jobs in Lorton, VA (NOW HIRING)

Senior Analytics Engineer

Washington, DC ยท On-site

$93K - $120K/yr

This role focuses on analytics engineering and data modeling, not traditional pipeline-heavy data engineering. We are looking for someone who understands the why behind the data, not just the how

Principal Analytics Engineer

Arlington, VA ยท On-site

$190K - $220K/yr

Manage team of analytics engineers working with cross-functional stakeholders. * Ensure Forterra is on the cutting edge of robotics analytics. * Manage data governance for analytics and collaborate ...

Lead Data Analytics Engineer

Washington, DC ยท Remote

$160K - $230K/yr

Lead Data Analytics Engineer Remote/Work from Home within the United States Must be a U.S. Citizen with an active or interim Secret Clearance. @Orchard LLC has an immediate need for a Lead Analytics ...

Ability to provide clear guidance to others The team Our Data Engineering team helps build and modernize data platforms that support analytics, reporting, and business decision-making across complex ...

New

Ability to provide clear guidance to others The team Our Data Engineering team helps build and modernize data platforms that support analytics, reporting, and business decision-making across complex ...

New

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Analytics Engineer information

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.

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 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.

Do analytics engineers make good money?

Analytics engineers typically earn competitive salaries that vary by experience, location, and industry. They often have skills in SQL, data modeling, and tools like Python or Spark, which can contribute to higher compensation. Overall, the role is considered well-paying within the data and analytics field.

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 business insights.

What job categories do people searching Analytics Engineer jobs in Lorton, VA look for?

The top searched job categories for Analytics Engineer jobs in Lorton, VA are:

What cities near Lorton, VA are hiring for Analytics Engineer jobs?

Cities near Lorton, VA with the most Analytics Engineer job openings:

Infographic showing various Analytics Engineer job openings in Lorton, VA as of August 2026, with employment types broken down into 87% Full Time, 9% Part Time, and 4% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution.

Senior Analytics Engineer

Washington, DC โ€ข On-site

$93K - $120K/yr

Full-time

Re-posted 26 days ago


Job description

Our Story

About You:You are a high achiever looking to thrive in a fast-paced environment. You take pride in your own work but are comfortable collaborating with a team of highly motivated individuals. You can communicate clearly and concisely with teammates and clients, and you enjoy strong company culture and camaraderie. You can navigate multiple corporate functions, including global lines of service and corporate centers of excellence. You possess strong interpersonal skills and are willing to take on diverse tasks to achieve the team's common goal. You value personal and professional growth and are ready to take the next step in advancing your career.If this sounds like you, well, then you will love the culture at Avison Young!About Us:Avison Young is a global commercial real estate brokerage and advisory firm, offering transaction, management, financial and consulting services. We've designed our corporate structure to best serve our clients by enhancing collaboration across our organization.Real estate can have an enormous positive impact on people's lives - and we're in the business of making spaces and places work better for people. Our purpose is to create real economic, social and environmental value as a global real estate advisor, powered by people.We care about each other and we have each other's backs. This makes Avison Young a great place to be a client, and a great place to work. We support the whole person and their complete wellness - economic, mental and physical - because what's best for our business comes from our people bringing their whole selves to work.

Of course we love it here, but outsiders think we're pretty great too! Avison Young has been recognized as one of Canada's Best Managed Companies for the 13th year in a row, with a Platinum Club designation!ย 

Overview

Join Avison Young's Data Architecture team as a Senior Analytics Engineer, where you will own and scale our analytics layer in Snowflake using dbt. This is a hands-on leadership role focused on building high-quality, business-aligned data models that power reporting, analytics, and data products across the organization.

You will act as a player-coach, balancing hands-on development with leadership of other engineers, while partnering closely with business stakeholders to define metrics, data models, and semantic consistency across the company. Your work will directly enable better decision-making by ensuring data is not just available, but trusted, well-structured, and meaningful.

This role focuses on analytics engineering and data modeling, not traditional pipeline-heavy data engineering. We are looking for someone who understands the why behind the data, not just the how.

What we value in a business analyst:

  • Customer-focused: You prioritize building data products and models that are intuitive, trusted, and drive real business outcomes.
  • Attention to detail: You ensure data accuracy, consistency, and quality across complex transformations and models.
  • Diverse thoughts: You collaborate effectively, incorporate feedback, and value multiple perspectives in shaping data solutions.
  • Team player & leader: You lead by example-mentoring others, setting standards, and contributing hands-on alongside your team.
  • Pragmatic: You balance speed and quality, making smart trade-offs without compromising long-term maintainability.
  • Data product mindset: You treat datasets as products, with clear ownership, definitions, and accountability.
  • Global teammate: Comfortable working in a collaborative, distributed team environment.

The base salary is aligned with market data and is estimated between $93,000 to $120,000 with the ability to achieve additional compensation through bonus.ย  This salary range reflects base compensation for the position across all US locations. Within this range, individual pay is determined by work location and other factors, including relevant education/training, experience, and internal equity.

Responsibilities

Analytics Engineering & Data Modeling (Core Focus):

  • Design, develop, and maintain scalable, business-aligned data models in Snowflake using dbt (staging, intermediate, marts layers)
  • Define and enforce semantic consistency, including metrics, dimensions, and KPIs across the organization
  • Build and manage dbt projects, including models, tests, documentation, and lineage
  • Design, deploy, and maintain Snowflake Cortex Search and semantic models to provide high-quality, governed data structures for LLM-powered applications and AI initiatives
  • Oversee development operations and deployments of the data platform
  • Translate business requirements into well-structured, reusable data models
  • Implement data quality testing, validation, and documentation to ensure trusted data
  • Optimize query performance and transformation efficiency in Snowflake
  • Establish and enforce data modeling standards, best practices, and design patterns
  • Develop reusable analytics components to accelerate data product development

Data Product & Stakeholder Engagement:

  • Partner with business stakeholders to define metrics, KPIs, and data definitions
  • Ensure alignment between business needs and technical implementations
  • Contribute to the development of data products and semantic layers that support analytics and reporting
  • Drive adoption and usability of data models across analytics and business teams

Leadership & Team Responsibilities (Player-Coach):

  • Lead and mentor a small team of analytics/data engineers
  • Set standards for dbt development, code reviews, testing, and documentation
  • Contribute hands-on to development (~60-70%) while guiding team delivery
  • Drive team productivity, technical direction, and project execution
  • Support Agile processes, including backlog prioritization and sprint planning

Coordination & Delivery:

  • Gather and refine business requirements for data initiatives
  • Translate business needs into clear technical requirements and user stories
  • Support deployment, environment management, and release processes
  • Ensure high-quality delivery through testing, validation, and stakeholder alignment
Qualifications
  • 5+ years of experience in analytics engineering, data engineering, or related roles
  • Strong expertise in SQL and data warehousing concepts
  • Proven experience with dbt and Snowflake (required)
  • Strong experience in dimensional data modeling (star schema, marts, semantic layers)
  • Experience building and maintaining analytics-ready data models and transformations
  • Demonstrated ability to lead projects or mentor team members in a player-coach capacity
  • Experience with data quality, testing frameworks, and documentation practices
  • Familiarity with Airflow / Astronomer or similar orchestration tools
  • Experience working with data pipelines, ETL/ELT processes, and cloud data platforms
  • Strong analytical thinking and ability to connect data solutions to business outcomes
  • Bachelor's degree in Information Technology, Business, or a related field, or equivalent experience

Nice to have:

  • Experience in commercial real estate, geospatial data, or location-based analytics
  • Experience building data products or semantic layers for BI tools
Workplace TypeOn-SiteOur Equal Opportunity Commitment

Avison Young practices as an equal opportunity employer in all services locations around the world. ย We are committed to building and maintaining a workforce diverse in experience, skills and knowledge with uniformity in service excellence, commitment and integrity.ย 

The firm maintains a strict policy to ensure employment opportunities are equal and do not discriminate based on race, color, religion, creed, age, sex, gender, gender identity or expression, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, protected veteran or military service status, or any other elements protected by law.

Avison Young welcomes and encourages applications from people with disabilities.ย Accommodations are available upon request for candidates during the recruitment process. For those requiring assistance, information relating to the need for accommodation and accommodation measures will be addressed confidentially.ย 

Avison Young is committed to employing the best talent with the most fair and equitable recruitment practices.ย Apply with us TODAY!ย 

Employment Type: FULL_TIME