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Analytics Engineer Jobs in Edmonds, WA (NOW HIRING)

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

THE ROLE As a Analytics Engineering Analyst, you will help identify promising markets, companies, products, operators, and investment or growth opportunities. You will turn ambiguous information into ...

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

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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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:
Infographic showing various Analytics Engineer job openings in Edmonds, WA as of August 2026, with employment types broken down into 87% Full Time, 7% Part Time, and 6% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Director,AI, Analytics & Engineering

Fortive

Everett, WA • On-site

Full-time

Re-posted 7 days ago


Fortive rating

7.3

Company rating: 7.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

Title: Director, AI, Analytics & Engineering

Location: United States (3 days in the Everett office)

Role Summary
The Director, AI, Analytics & Engineering leads the enterprise AI, data, analytics, and AI/data engineering function within the CIO organization, with end-to-end accountability for turning AI experimentation into secure, governed, production-grade capabilities that deliver measurable business outcomes. 
This role owns enterprise data platforms and analytics, AI platforms and enablement, AI production delivery, and the operating model required to scale adoption across IT and business teams. 
The leader serves as a primary partner to product and engineering organizations to promote AI reuse, shared platforms, and consistent delivery standards, while ensuring AI use is responsible, compliant, and aligned to enterprise governance and decision rights. 

Key Responsibilities
Own strategy, delivery, and scalability of enterprise analytics, data platforms, AI solutions, and data/AI engineering capabilities, with accountability for measurable business outcomes. 
Define and drive the enterprise AI roadmap and execution plan, converting pilots and proofs-of-concept into high-value production solutions embedded into business workflows. 
Establish and operate a clear AI intake and engagement model, including standardized intake channels, feasibility assessment, benefit quantification, and resourcing decisions tied to enterprise priorities. 
Ensure qualified AI requests enter portfolio visibility and resource allocation mechanisms (e.g., Lean Portfolio Management), and drive prioritization tradeoffs to maximize impact. 
Set decision rights and enforce accountability boundaries across AI platforms and solutions: technical standards and platform roadmap owned by the AI team; risk acceptance and compliance owned by Security/Privacy/Legal; outcomes and adoption owned by business owners. 
Enforce governed AI enablement across cloud environments by defining technical standards, reference architectures, and guardrails for data access, model use, logging, monitoring, and auditability. 
Partner with Security, Privacy, and Legal to operationalize responsible AI practices, including acceptable use expectations and governance processes for approving internal AI tools and features. 
Reduce AI and analytics tool sprawl by consolidating platforms, retiring shadow solutions, and standardizing reusable patterns and shared components. 
Own the enterprise data warehouse and analytics ecosystem, ensuring trusted data, scalable pipelines, consistent data quality, and decision-ready analytics products and dashboards. 
Establish engineering excellence for AI and data products, including reliability practices, lifecycle management, availability/performance expectations, and cost efficiency. 
Define and run standard work for delivery planning, execution cadence, escalation, and executive reporting to ensure predictable outcomes and rapid issue resolution. 
Own value realization and success metrics for AI and analytics delivery, including business value delivered, platform adoption/usage, time-to-MVP and time-to-production, quality/risk metrics, and reuse of shared platforms and components. 
Own portfolio and financial accountability for AI and analytics investments, including budget planning, vendor/tooling decisions, and run vs. grow allocation aligned to outcomes. 
Evangelize AI practices across the enterprise through office hours, enablement, community forums, and practical guidance that accelerates adoption while keeping governance embedded in delivery. 
Serve as the CIO organization's executive liaison to product and engineering teams to promote AI adoption, shared patterns (platform-first), and scalable productionization approaches. 
Build and lead a high-performing organization across AI engineering, data engineering, analytics, and platforms; establish hiring profiles, capability plans, and a vendor strategy that strengthens internal competence over time. 
Clearly define what is out of scope and enforce it (e.g., no AI delivery without a defined business owner and success metrics; no enablement outside approved governance guardrails; no long-term ownership of bespoke, non-strategic solutions). 
Communicate crisply with senior leadership on outcomes delivered, investment tradeoffs, risks, compliance posture, and progress against delivery KPIs (on-time/on-scope, time to production, quality, and cost per unit of delivery).

Role Characteristics
Enterprise-wide leadership role with direct accountability for platforms, governance, delivery operating model, and measurable outcomes across AI, analytics, and data engineering. 
Balances innovation and experimentation with production rigor, compliance, and cost discipline. 

Qualifications and Experience
15+ years of leadership experience across AI, data engineering, analytics, and modern platform delivery. 
Proven track record scaling AI from pilots to enterprise-grade, secure production solutions with repeatable delivery patterns. 
Deep experience with enterprise data platforms, data warehousing, pipelines, and analytics product delivery (trusted metrics, dashboards, decision-ready insights). 
Demonstrated ability to establish AI governance, decision rights, responsible AI practices, and embedded compliance mechanisms. 
Experience building and running intake, prioritization, and engagement models that quantify benefits and drive portfolio decisions. 
Strong engineering leadership capability to set standards for reliability, lifecycle management, and operational readiness of AI/data products. 
Proven executive presence and ability to partner with product and engineering organizations to embed AI capabilities into products and workflows. 
Strong financial and portfolio management skills, including investment tradeoffs, vendor/tool strategy, and outcome-based value tracking. 

Success Measures

  • AI and analytics investments consistently deliver measurable business outcomes, with clear ownership, quantified value, and disciplined prioritization. 
  • AI governance enables speed with trust through embedded guardrails, clear decision rights, and responsible AI adoption at scale. 
  • Data platforms and analytics produce trusted, decision-ready insights with strong reliability, reuse, and reduced tool sprawl.
  • Time-to-MVP and time-to-production improve while quality, compliance posture, and cost efficiency remain strong and visible to leadership.

Scope Guardrails
This role is accountable for enterprise AI, analytics, and data platforms, governance, operating model, and value realization within the CIO organization. It does not own product roadmaps, product P&L, or embedded product engineering teams, which remain the responsibility of Product and Engineering organizations. The role enables, governs, and scales AI capabilities through shared platforms, standards, tooling, and delivery models, while partnering with Product and Engineering teams to embed AI into products and workflows. The role does not operate as a centralized service for bespoke or oneoff solutions and will not approve or deliver AI initiatives without a defined business owner, quantified outcomes, and adherence to enterprise governance. The role has authority to approve, prioritize, standardize, or retire AI and analytics platforms and tools, but adoption success and business impact are jointly owned with business and product leaders.

Fortive Corporation Overview

Fortive's essential technology makes the world stronger, safer, and smarter. We accelerate transformation across a broad range of applications including environmental, health and safety compliance, industrial condition monitoring, next-generation product design, and healthcare safety solutions.

We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in software-powered workflow solutions, data-driven intelligence, AI-powered automation, and other disruptive technologies. We're a force for progress, working alongside our customers and partners to solve challenges on a global scale, from workplace safety in the most demanding conditions to groundbreaking sustainability solutions.

We are a diverse team 18,000 strong, united by a dynamic, inclusive culture and energized by limitless learning and growth. We use the proven Fortive Business System (FBS) to accelerate our positive impact. 

At Fortive, we believe in you. We believe in your potential-your ability to learn, grow, and make a difference. 

At Fortive, we believe in us. We believe in the power of people working together to solve problems no one could solve alone. 

At Fortive, we believe in growth. We're honest about what's working and what isn't, and we never stop improving and innovating.

Fortive: For you, for us, for growth.

About Fluke

Fluke is leading the world in creating software, test tools and technology that will support customers today and in the future. We are a customer-obsessed market leader with a strong reputation for reliability, quality and safety.  

A wholly owned subsidiary of Fortive Corporation (www.fortive.com), Fluke is a global corporation headquartered in the greater Seattle area. Driven by the successful Fortive Business System, Fluke offers the passion of a startup with the resources of a Fortune 500 company. We are focused on the growth of our individual employees, teams and the Fluke brand.

We Are an Equal Opportunity Employer
 
Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at applyassistance@fortive.com.  

What Fortive employees say

Pay

Hours and flexibility

Workplace

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About Fortive

Sourced by ZipRecruiter

Fortive is a diversified technology company that operates across multiple industries, delivering innovative solutions and products that empower businesses to enhance their productivity and operational efficiency. With a strong portfolio of industry-leading brands, Fortive focuses on creating intelligent, connected devices and software that enable precise measurement, control, and optimization. Fortive's expertise spans various sectors, including industrial automation, transportation, healthcare, and retail. Through advanced technologies and solutions, Fortive help customers automate processes, improve quality and safety, and drive overall performance. Whether it's precision measurement instruments, sensing technologies, or software platforms, Fortive provides reliable and scalable solutions that meet the evolving needs of their customers.

Industry

Electrical equipment, appliance, and component manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Everett, WA, US

Year founded

2016

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