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Ai Data Analytics Jobs in Renton, WA (NOW HIRING)

1 point system

AI Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

Requirement - AI Data Engineer Location- Redmond WA 98052-Hybrid Contract W2 Top 3 Must-Have Hard ... Minimum 5 years of experience designing and developing reporting and analytics solutions. * Hands ...

1 point system

AI Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

Top 3 Must-Have Hard Skills 1. Reporting & Analytics - 5+ Years * Minimum 5 years of experience ... Description The main function of an AI Data Engineer is to design, develop, enhance, validate ...

Munich Re

Technical Architect - Data, Analytics & AI

Kent, WA · Hybrid

$72 - $92.50/hr

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework , with a ...

Purple Hires

AI Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

**Top 3 Must-Have HARD Skills** **1. Reporting & Analytics** -- **5+ years** * Power BI * Data Modeling * DAX * Grafana or similar reporting platforms * HTML/Web-based reports **2. Automation, AI ...

New

Team Red Dog

AI Data Engineer 3

Redmond, WA · On-site

$128K - $154K/yr

This opportunity is expected to focus on enterprise data engineering, cloud-based analytics infrastructure, ETL/ELT development, and AI/ML-driven data initiatives supporting large-scale business ...

Team Red Dog

AI Data Engineer 3

Redmond, WA · On-site

$128K - $154K/yr

This opportunity is expected to focus on enterprise data engineering, cloud-based analytics infrastructure, ETL/ELT development, and AI/ML-driven data initiatives supporting large-scale business ...

BC Forward

AI Data Engineer 3

Redmond, WA · On-site

$65/hr

Applications Dev & Test - AI Data Engineer 3 Location: Redmond, WA Duration: 13 months+ Pay Range ... We are seeking a Senior Analytics Engineer to join our dynamic Player and Data Analytics team. The ...

OTSI

AI & Data Solutions Architect

Seattle, WA · Remote

Architect scalable, cloud-native software solutions and modern data platforms (e.g Microsoft Fabric, Databricks, Snowflake) aligned with enterprise analytics and AI initiatives. Delivery Oversight ...

OTSI

AI & Data Solutions Architect

Seattle, WA · On-site

Microsoft Fabric, Databricks, Snowflake) aligned withenterprise analytics and AI initiatives. * Delivery Oversight &Hands-On Execution: Provide technical leadership to global development and data ...

Deloitte

Agentic AI, AI & Data Science Engineer

Seattle, WA

$130K - $156K/yr

We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively. Qualifications Required: * 4+ years of experience delivering AI ...

New

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How much do ai data analytics jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for ai data analytics in Renton, WA is $61.58, according to ZipRecruiter salary data. Most workers in this role earn between $49.47 and $69.76 per hour, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior data scientist, AI research director, or machine learning executive, often requiring advanced skills, extensive experience, and sometimes equity or bonuses. These roles are usually found in large tech companies or startups with significant AI investments and may involve leadership, strategic planning, and specialized knowledge of tools like Python, TensorFlow, or cloud platforms.

Which 3 jobs will survive AI?

Data analysts, AI specialists, and cybersecurity professionals are expected to remain in demand as AI advances. These roles require critical thinking, complex problem-solving, and specialized skills that are difficult to automate fully. Continuous learning and proficiency with AI tools can enhance job security in these fields.

What is the difference between Ai Data Analytics vs Data Scientist?

AspectAi Data AnalyticsData Scientist
Required CredentialsBachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analyticsBachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred
Work EnvironmentTech companies, finance, healthcare; focus on AI-driven data analysisResearch labs, tech firms, finance; focus on data modeling and insights
Employer & Industry UsageUsed in industries leveraging AI for predictive analytics and automationUsed across industries for data modeling, predictive analytics, and research

Ai Data Analytics professionals focus on applying AI techniques to analyze data and develop automated solutions, while Data Scientists build models and interpret data to generate insights. Both roles require strong analytical skills and familiarity with data tools, but Ai Data Analytics emphasizes AI implementation, whereas Data Scientists focus on statistical modeling and research.

How does an AI Data Analytics professional typically collaborate with cross-functional teams within an organization?

AI Data Analytics professionals frequently work alongside departments such as marketing, operations, IT, and product development to interpret complex datasets and provide actionable insights. Collaboration often involves translating business needs into data-driven solutions, communicating findings in accessible terms, and ensuring that analytics projects align with organizational goals. Effective teamwork and clear communication are crucial, as analytics professionals must bridge the gap between technical data analysis and practical business application.

What is the salary of an AI data analyst?

The salary of an AI data analyst typically ranges from $60,000 to $120,000 annually, depending on experience, location, and industry. Professionals with advanced skills in machine learning, programming, and data visualization tools tend to earn higher salaries.

What are the key skills and qualifications needed to thrive as an AI Data Analyst, and why are they important?

To thrive as an AI Data Analyst, you need a strong background in statistics, data analysis, and machine learning, typically supported by a degree in computer science, mathematics, or a related field. Proficiency with tools such as Python, R, SQL, and data visualization platforms like Tableau, along with knowledge of AI frameworks such as TensorFlow or PyTorch, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and present actionable insights to stakeholders. These skills are crucial for driving data-driven decision-making and maximizing the impact of AI initiatives within organizations.

What is AI Data Analytics?

AI Data Analytics refers to the use of artificial intelligence technologies to analyze and interpret large volumes of data. By leveraging machine learning algorithms, natural language processing, and other AI methods, professionals in this field can uncover patterns, make predictions, and drive data-driven decision-making. AI Data Analytics is widely used across industries to optimize operations, improve customer experiences, and gain competitive insights. The role typically involves working with big data platforms, developing models, and communicating findings to stakeholders.

What does an AI data analyst do?

An AI data analyst collects, processes, and analyzes large datasets to extract insights that inform business decisions. They use tools like Python, R, and machine learning algorithms to identify patterns and trends, often working closely with data engineers and data scientists in a collaborative environment.
What job categories do people searching Ai Data Analytics jobs in Renton, WA look for? The top searched job categories for Ai Data Analytics jobs in Renton, WA are:
What cities near Renton, WA are hiring for Ai Data Analytics jobs? Cities near Renton, WA with the most Ai Data Analytics job openings:
Ai Data Analytics jobs near you
AI Data Engineer

AI Data Engineer

1 point system

Redmond, WA • On-site

$128K - $154K/yr

Contractor

Posted 7 days ago

Job description

Requirement - AI Data Engineer

Location- Redmond WA 98052-Hybrid

Contract W2

Top 3 Must-Have Hard Skills

 

1. Reporting & Analytics – 5+ Years

  • Minimum 5 years of experience designing and developing reporting and analytics solutions.
  • Hands-on expertise with Power BI, Data Modeling, and DAX.
  • Experience with Grafana or similar reporting/dashboard platforms.
  • Ability to develop and maintain HTML/web-based reports.

2. Automation, AI & Agentic Solutions – 3+ Years

  • Minimum 3 years of experience in automation and AI-driven engineering solutions.
  • Strong programming skills in Python, C#, and PowerShell.
  • Experience with AI-assisted engineering tools, Copilot/Agentic platforms, and automated report generation.

3. Data Engineering – 5+ Years

  • Minimum 5 years of experience in data engineering and data integration.
  • Strong proficiency in SQL, ETL processes, and data pipeline development.

Typical Day in the Role

  • Purpose of the Team: The purpose of this team is to provide telemetry reporting, analytics, automation, and AI-driven insights that improve visibility into service health, availability, and operational performance through dashboards, reporting solutions, and data engineering capabilities.
  • Key projects: This role will contribute to telemetry and service health initiatives by developing reporting, analytics, and automation solutions. Responsibilities include building Power BI reports and Grafana dashboards, creating Kusto-based analytics, supporting telemetry monitoring, and improving data-driven insights related to availability and operational health.

Candidate Requirements

  • Disqualifiers: Candidates with limited or no experience in reporting and analytics, automation, AI-assisted solutions, data engineering, Power BI, Grafana, or Kusto-based data analysis will not be eligible for the role.
  • Best vs. Average: The ideal resume will contain hands-on experience with telemetry and analytics platforms, including Power BI, Grafana, SQL/Kusto, Python, PowerShell, or C#, along with expertise in data engineering, ETL/data pipelines, automation, and AI-assisted reporting solutions. Experience supporting telemetry health, availability monitoring, operational dashboards, and enterprise-scale reporting environments is highly preferred.

Description

The main function of an AI Data Engineer is to design, develop, enhance, validate, maintain, and support telemetry reporting, data solutions, automation, and AI-assisted solutions. The role develops reports, dashboards, data models, automation, reporting & analytics agent components, and supporting data solutions to improve telemetry coverage, telemetry availability, clean telemetry, and telemetry data quality.

 

Job Responsibilities

  • Design, develop, and maintain telemetry reporting, data solutions, automation, and AI-assisted solutions.
  • Design, develop, and enhance Power BI reports, Grafana dashboards, semantic models, and analytics solutions to deliver actionable business insights.
  • Develop and optimize Azure Data Explorer (Kusto/ADX) queries, functions, data models, scheduled tables, materialized tables, snapshot tables, and supporting datasets.
  • Integrate enterprise data sources and develop supporting SQL queries, ETL processes, and data pipelines required for analytics and reporting solutions.
  • Develop automation solutions using Python, PowerShell, C#, or similar scripting/programming languages to automate operational tasks and support business requirements.
  • Develop AI-enabled reporting and analytics agent components, including Copilot Agents, Agency CLI skills, prompt assets, and supporting knowledge files.
  • Validate data quality, business logic, report accuracy, dashboards, and scheduled refreshes to ensure reliable production solutions.
  • Monitor, troubleshoot, and resolve data pipeline, query, reporting, and production issues to maintain solution reliability and performance.
  • Create and maintain technical documentation, reusable components, and engineering best practices to support long-term solution maintainability.
  • Collaborate with cross-functional engineering teams to deliver scalable, high-quality analytics and reporting solutions.