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Senior Dataops Engineer Jobs in Everett, WA (NOW HIRING)

AWS Data Engineer (Associate)

Seattle, WA ยท On-site +1

$130K - $156K/yr

Understanding of DataOps Engineering How we work? We run a forward-deployed model. Engineers embed ... As an associate, you'll work inside that model from day one shipping alongside senior engineers ...

AWS Data Engineer (Associate)

Seattle, WA ยท Remote

$117K - $140K/yr

Understanding of DataOps Engineering How we work? We run a forward-deployed model. Engineers embed ... As an associate, you'll work inside that model from day one shipping alongside senior engineers ...

AWS Data Engineer (Associate)

Seattle, WA

$130K - $156K/yr

Understanding of DataOps Engineering How we work? We run a forward-deployed model. Engineers embed ... As an associate, you'll work inside that model from day one shipping alongside senior engineers ...

Senior Business Analytics Specialist

Redmond, WA ยท On-site

$62 - $79.75/hr

We are seeking a technical Senior Business Analytics Specialist to help build and operate the next ... Engineering & DataOps: Git, Fabric deployment pipelines, CI/CD (Azure DevOps / GitHub), automated ...

Senior Dataops Engineer information

See Everett, WA salary details

$65.7K

$139.8K

$202.7K

How much do senior dataops engineer jobs pay per year?

As of Aug 2, 2026, the average yearly pay for senior dataops engineer in Everett, WA is $139,804.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,400.00 and $158,500.00 per year, depending on experience, location, and employer.

What are some common challenges a Senior DataOps Engineer faces when scaling data infrastructure for a growing organization?

A Senior DataOps Engineer often encounters challenges such as ensuring data pipeline reliability during rapid scaling, managing increasing data volume and complexity, and maintaining high data quality across distributed environments. Balancing automation with flexibility, integrating new tools with legacy systems, and coordinating with cross-functional teams (like data scientists and DevOps) are also key hurdles. Success in this role requires proactively identifying bottlenecks, optimizing workflows, and fostering a culture of collaboration to support evolving business needs.

What are the key skills and qualifications needed to thrive as a Senior DataOps Engineer, and why are they important?

To thrive as a Senior DataOps Engineer, you need a solid background in data engineering, automation, CI/CD pipelines, and strong knowledge of data architecture, usually supported by a degree in computer science or a related field. Expertise in tools like Apache Airflow, Kubernetes, Docker, cloud platforms (AWS, Azure, or GCP), and proficiency with scripting languages such as Python or Bash are typically required, along with certifications like AWS Certified Solutions Architect or Google Cloud Data Engineer. Outstanding problem-solving skills, collaboration, and effective communication are essential soft skills for integrating diverse teams and managing complex workflows. These capabilities ensure data reliability, streamlined operations, and scalable solutions in dynamic data-driven environments.

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

AspectSenior Dataops EngineerData Engineer
CredentialsTypically requires experience with cloud platforms, scripting, and data pipeline toolsRequires knowledge of database systems, SQL, and data modeling
Work EnvironmentFocuses on deployment, automation, and maintaining data infrastructureDesigns and builds data pipelines and storage solutions
Industry UsageCommon in organizations emphasizing data operations and automationWidespread across industries for data storage and processing

The main difference is that Senior Dataops Engineers focus on managing and automating data workflows and infrastructure, while Data Engineers primarily design and build data pipelines and storage systems. Both roles require strong technical skills, but their focus areas differ within the data ecosystem.

What are Senior DataOps Engineers?

Senior DataOps Engineers are experienced professionals who design, implement, and manage data pipelines and workflows to ensure reliable, efficient, and scalable data operations within an organization. They bridge the gap between data engineering, DevOps, and analytics by automating data integration, deployment, and monitoring processes. Their role often includes optimizing data infrastructure, ensuring data quality, and enabling data teams to quickly deliver insights. Senior DataOps Engineers also mentor junior team members and help define best practices for data operations.
What are popular job titles related to Senior Dataops Engineer jobs in Everett, WA? For Senior Dataops Engineer jobs in Everett, WA, the most frequently searched job titles are:
What job categories do people searching Senior Dataops Engineer jobs in Everett, WA look for? The top searched job categories for Senior Dataops Engineer jobs in Everett, WA are:
What cities near Everett, WA are hiring for Senior Dataops Engineer jobs? Cities near Everett, WA with the most Senior Dataops Engineer job openings:

AWS Data Engineer (Associate)

Mactores

Seattle, WA โ€ข On-site, Remote

$130K - $156K/yr

Full-time

Re-posted 28 days ago


Job description

Mactores is the agent-native AWS modernization firm. Most modernization work doesn't ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores' founders' sister company, which absorbs the repetitive 60-70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.
This role sits in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us with pipelines nobody trusts, metrics nobody agrees on, and warehouses that stall every new business question. You'll build the data products that fix that - working with business leads, analysts, and data scientists to understand the domain, then shipping pipelines and models that hold up in production.
Because Aedeon handles the repetitive layer source discovery, schema mapping, validation harnesses - you won't spend your early career grinding through spreadsheet audits. You'll spend it writing code that reaches production and learning judgment from engineers who own cutovers. Data quality isn't a checkbox here; it's the product.
What you will do?
  • Write efficient PySpark and Amazon Glue code that ships to production.
  • Write SQL in Amazon Athena and Amazon Redshift.
  • Pick up new technologies and techniques and put them to work on real business problems.
  • Work across engineering and business teams to build data products and services people actually use.
  • Deliver projects with the team and land customer updates on time.

What are we looking for?
  • 1 to 3 years of experience in Apache Spark, PySpark, and Amazon Glue.
  • 2+ years of experience writing ETL jobs using PySpark and SparkSQL.
  • 2+ years of experience with SQL queries and stored procedures.
  • Deep understanding of the Dataframe API and the transformation functions supported by Spark 2.7+.

You will be preferred if you have
  • Prior experience in working on AWS EMR, Apache Airflow
  • Certifications AWS Certified Big Data - Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer
  • Understanding of DataOps Engineering

How we work?
We run a forward-deployed model. Engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally. Aedeon absorbs scale; engineers absorb judgment; the contract absorbs risk. As an associate, you'll work inside that model from day one shipping alongside senior engineers rather than watching from a bench. The culture is casual and steers clear of rigid corporate habits. We care about what ships, and we let you be yourself while you ship it.
Life at Mactores
We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.
1. Be one step ahead
2. Deliver the best
3. Be bold
4. Pay attention to the detail
5. Enjoy the challenge
6. Be curious and take action
7. Take leadership
8. Own it
9. Deliver value
10. Be collaborative
We would like you to read more details about the work culture on https://mactores.com/careers
The Path to Joining the Mactores Team
At Mactores, our recruitment process is structured around three distinct stages:
Pre-Employment Assessment:
A series of evaluations of your technical proficiency and suitability for the role.
Managerial Interview: The hiring manager engages with you in multiple discussions, 30 minutes to an hour each, covering technical skills, hands-on experience, leadership potential, and communication.
HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.
Mactores provides equal opportunities in all employment practices. We don't discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This applies to every part of the employment relationship, recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs.
Note: Please answer as many questions as possible with this application to accelerate the hiring process.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.