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Analytics Engineer Jobs in Edmonds, WA (NOW HIRING)

1 point system

AI Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

Identify and analyse multi-structured data or metadata from a variety of sources to select and ... Leverage modern data engineering practices and frameworks with an object-oriented approach to ...

Hasbro

Director Analytics WOTC

Renton, WA · Hybrid

Lead business intelligence engineering and analytics talent across multiple domains. * Mentor and develop team members while promoting excellence, collaboration, and innovation. * Own the analytics ...

Protingent

Thermal Analysis Engineer

Bellevue, WA · On-site

$52 - $85/hr

Reactor Enclosure System (RES) Thermal Analysis Engineer Position Description: Protingent Staffing has an exciting contract Reactor Enclosure System (RES) Thermal Analysis Engineer opportunity. Job ...

System One

Thermal Analysis Engineer

Bellevue, WA · Remote

$52 - $85/hr

Thermal Analysis Engineer Type: Contract (6 months) Compensation: $52 - $85 hourly Contractor Work Model: Fully Remote System One is seeking a highly motivated Thermal Analysis Engineer. Tasks

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All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Edmonds, WA

Analytics Engineer information

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 job categories do people searching Analytics Engineer jobs in Edmonds, WA look for? The top searched job categories for Analytics Engineer jobs in Edmonds, WA are:
What cities near Edmonds, WA are hiring for Analytics Engineer jobs? Cities near Edmonds, WA with the most Analytics Engineer job openings:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Edmonds, WA as of August 2026, with employment types broken down into 92% Full Time, and 8% Contract. Highlights an 88% In-person, and 12% Remote job distribution.

AI Data Engineer

1 point system

Redmond, WA • On-site

$128K - $154K/yr

Contractor

Re-posted 4 days ago

Job description

Candidate Requirements

Disqualifiers: Repetitive, overly long, or generic or keyword heavy resumes that lack context on impact or outcomes (ex, just listing tools/tech without explaining business value) will likely be disqualified

Best vs. Average: The ideal resume would contain resumes that clearly demonstrate how their work drives business impact (ex. improved performance, enabled decision making, supported marketing or product outcomes) and show strong critical thinking and problem solving in how they present their experience.

Top 3 Must-Have HARD Skills & years of experience for each:   

  1. Python 4-5 years
  2. Data Modeling 3 years
  3. Marketing 2 years

Responsibilities

  • Build subject matter expertise of our business and data domains to collaborate with data consumers and stakeholders to understand their information needs and assist them with data access.
  • Identify and analyse multi-structured data or metadata from a variety of sources to select and document the most effective and accurate data which fulfils the analytics requirements.
  • Design data models, architect dataflows, and develop abstractions to deliver scalable solutions for analytics and machine learning ensuring they can evolve with changing needs.
  • Leverage modern data engineering practices and frameworks with an object-oriented approach to architect, build, and maintain automated data pipelines which transform data into clean, enriched, and accurate information.
  • Advance our infrastructure by developing frameworks, reusable components and new capabilities to achieve our mission.
  • Enable the Franchise performance marketing strategy through the development of relevant and robust data products.

 

Required Qualifications

  • Bachelor's Degree in Computer Science, Software Engineering, Computer Engineering, or related field AND 4+ years’ experience in analytics engineering, data engineering, data science, data analyst, or related software development work
  • Master's Degree in Computer Science, Software Engineering, Computer Engineering, or related field AND 3+ years’ experience in analytics engineering, data engineering, data science, data analyst, or related software development work
  • OR equivalent experience.
  • 2+ years working as an Analytics Engineer or Data Engineer with regular business collaboration or equivalent on large enterprise systems.
  • Experience building, maintaining and optimizing enterprise scale data pipelines handling logs and event streaming data on Cloud Data Platforms using modern tools like Spark, and airflow; Azure preferred.
  • Proficiency with SQL; Advanced skills with Python for data transformation and automation

 

Preferred Qualifications

  • Critical thinker and problem solver who brings a creative and open mindset.
  • A proven track record building and optimizing analytic solutions and data products which deliver significant business impact.
  • Data analysis and exploration skills to identify, select and prepare data for analytics.
  • Business acumen to address business challenges through analytics engineering.
  • Experience building, maintaining and optimizing enterprise scale data pipelines handling logs and event streaming data on Cloud Data Platforms using modern tools like Spark, and airflow; Azure preferred.
  • Working knowledge of DevOps and DataOps.