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Senior Data Engineering Jobs in Redmond, WA (NOW HIRING)

Noblesoft Technologies

Data Engineer

Seattle, WA · Remote

$117K - $140K/yr

Senior Data Engineer Location: Remote JD: Key Responsibilities * Design and implement ETL pipelines using Microsoft Fabric (Dataflows, Pipelines, Lakehouse, warehouse, sql) and Azure Data Factory.

The Walt Disney Company

Sr Data Engineer

Seattle, WA · On-site

$120K - $163K/yr

Additionally, itis responsible forthe data engineering, science, and products for Disney ... Role Summary The Senior Data Engineer will design, build, and optimize data pipelines and ...

JLL

Senior Data Engineer

Seattle, WA

$120K - $163K/yr

What this job involves As a Senior Data Engineer on the Data Consumption team, you will own the ... Qualifications and skills Required Qualifications * 5+ years of data engineering experience ...

Amgen

Sr. Data Scientist - Process Modeling

Seattle, WA · On-site

As a Sr. Data Scientist, you will evaluate and improve Amgen's digital assets, collaborating as ... Work closely with engineers to identify opportunities for process design improvements for Amgen ...

New

Valid8 Financial, Inc.

Sr. Data Architect

Seattle, WA · On-site

$150 - $170/hr

The Senior Data Architect plays a foundational role in building the data infrastructure that will ... Mentor and elevate data engineers, BI developers, and analysts, raising architectural maturity and ...

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Senior Data Engineering information

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How much do senior data engineering jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for senior data engineering in Redmond, WA is $63.63, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $75.38 per hour, depending on experience, location, and employer.

What is a senior data engineer?

A Senior Data Engineer is an experienced professional who designs, builds, and maintains scalable data systems and infrastructure within an organization. They are responsible for developing robust data pipelines, ensuring data quality, and optimizing data workflows to support analytics and business intelligence needs. Senior Data Engineers often mentor junior team members, collaborate with data scientists and analysts, and help establish best practices for data management. Their expertise enables organizations to efficiently store, process, and analyze large volumes of data for strategic decision-making.

What are the key skills and qualifications needed to thrive as a senior data engineer?

To thrive as a Senior Data Engineer, you need deep expertise in data modeling, ETL processes, programming (often Python, Java, or Scala), and a strong background in computer science or a related field. Proficiency with big data tools like Hadoop, Spark, SQL/NoSQL databases, and cloud platforms such as AWS, Azure, or GCP is typically required, along with relevant certifications. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior engineers. These skills ensure reliable, scalable data infrastructure that supports business intelligence and decision-making across the organization.

How does a senior data engineer typically collaborate with data scientists and analysts on projects?

As a Senior Data Engineer, you will frequently work alongside data scientists and analysts to design, build, and optimize data pipelines and infrastructure that support complex analytics and machine learning initiatives. Collaboration often involves translating business or analytical requirements into scalable data solutions, ensuring data quality, and enabling efficient access to large datasets. Regular communication and agile teamwork are essential, as you'll often participate in cross-functional meetings to align on project goals, resolve data issues, and support the deployment of analytical models into production environments.

What is the difference between Senior Data Engineering vs Data Engineer?

AspectSenior Data EngineerData Engineer
Required CredentialsBachelor's or Master's in CS, experience in data pipelines, cloud platformsBachelor's in CS or related field, foundational data skills
Work EnvironmentDesigning complex data systems, mentoring juniors, optimizing pipelinesBuilding and maintaining data pipelines, data ingestion, basic ETL tasks
Employer & Industry UsageTech companies, finance, healthcare, large enterprisesStartups, mid-sized companies, tech firms

Senior Data Engineers typically have more experience, handle complex data architecture, and mentor teams, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but Senior Data Engineers often take on leadership and strategic responsibilities.

What do senior data engineers do?

Senior data engineers design, build, and maintain large-scale data pipelines and infrastructure to support data collection, storage, and analysis. They often work with tools like SQL, Spark, and cloud platforms, and may lead data team projects while ensuring data quality and security.

What are the most commonly searched types of Data Engineering jobs in Redmond, WA?

The most popular types of Data Engineering jobs in Redmond, WA are:

What are popular job titles related to Senior Data Engineering jobs in Redmond, WA?

For Senior Data Engineering jobs in Redmond, WA, the most frequently searched job titles are:

What job categories do people searching Senior Data Engineering jobs in Redmond, WA look for?

The top searched job categories for Senior Data Engineering jobs in Redmond, WA are:

What cities near Redmond, WA are hiring for Senior Data Engineering jobs?

Cities near Redmond, WA with the most Senior Data Engineering job openings:

Senior Data Engineering jobs near you
Infographic showing various Senior Data Engineering job openings in Redmond, WA as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $132,345 per year, or $63.6 per hour.

Senior Data Engineer (AWS Databricks)

Seattle, WA • On-site

HMG America
IT Services • 11 - 50 employees
Learn more about HMG Americaexternal

$119K - $163K/yr

Other

Posted 4 days ago

Job description

HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Senior Data Engineer (AWS Databricks) in Seattle, WA / Dallas, TX / Phoenix, AZ / Charleston, SC. Below is the detailed job description.

Title: Senior Data Engineer (AWS Databricks)

Location: Seattle, WA / Dallas, TX / Phoenix, AZ / Charleston, SC (Hybrid . 1-2 days/ week)

Job Description:

ROLE OVERVIEW

We are looking for a Senior Data Engineer to own the design and delivery of modern data platforms built on AWS and Databricks. This role combines deep hands-on engineering, covering data ingestion, transformation, and warehousing across structured and unstructured sources.

KEY RESPONSIBILITIES

  • Deliver end-to-end data engineering solutions on AWS and Databricks, spanning ingestion, transformation, and warehousing layers.
  • Design scalable pipelines for structured and unstructured data, balancing reliability, performance, and cost efficiency.
  • Partner with architects and business stakeholders to translate requirements into robust, production-ready designs.
  • Establish and maintain standards for data quality, governance, and platform scalability.

WHAT WE'RE LOOKING FOR

MUST-HAVE SKILLS

AWS Services - Hands-on expertise across core AWS services spanning compute, storage, orchestration, and security in production environments.

Databricks Platform - Deep proficiency in Databricks, including Delta Lake, Unity Catalog, cluster management, and job orchestration at scale.

Data Engineering Lifecycle - Proven ability to design and operate ingestion, transformation, and warehousing pipelines across structured and unstructured data.

GOOD-TO-HAVE SKILLS

Agentic AI Exposure - Working understanding of agentic AI concepts and frameworks, and how they apply within modern data platforms.

Manufacturing Industry Knowledge - Familiarity with manufacturing industry data landscapes, processes, and common use cases.

Data Modelling - Understanding of data modelling principles, including dimensional and canonical modelling approaches.

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