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Full Time Ibm Data Engineer Jobs in Seattle, WA (NOW HIRING)

Sarian, Inc.

AWS Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Seattle, WA Onsite position Fulltime position *****NO Corp to Corp***** JD Design and Development: Design, develop, and implement data pipelines using AWS services such as AWS Glue, Lambda, S3 ...

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All JobsIbm Data Engineer JobsFull Time Ibm Data Engineer JobsFull Time Ibm Data Engineer Jobs in Seattle, WA

Full Time Ibm Data Engineer information

See Seattle, WA salary details

$50.6K

$147.6K

$202K

How much do full time ibm data engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for full time ibm data engineer in Seattle, WA is $147,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,300.00 and $156,500.00 per year, depending on experience, location, and employer.

What does a full time IBM data engineer do?

A Full Time IBM Data Engineer is responsible for designing, building, and maintaining data pipelines and architectures to support large-scale data processing within organizations using IBM technologies. They work with data integration, transformation, and storage solutions, ensuring data is accessible, reliable, and secure for analytics and business intelligence. Their role often includes collaborating with data scientists, analysts, and other IT professionals to optimize data workflows and implement best practices for data management.

What are the key skills and qualifications needed to thrive as a full time IBM data engineer?

To thrive as a Full Time IBM Data Engineer, you need strong skills in data modeling, SQL, programming languages like Python or Scala, and a relevant degree in computer science or engineering. Familiarity with IBM data platforms (such as IBM Db2, IBM Cloud Pak for Data, or IBM DataStage), big data frameworks, and certifications like IBM Certified Data Engineer are often required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with cross-functional teams and translating business needs into technical solutions. These competencies enable data engineers to design robust data pipelines, ensure data quality, and drive informed decision-making within organizations.

What are some common challenges faced by full time IBM data engineers, and how can they be addressed?

Full-time IBM Data Engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality, and optimizing data pipelines for performance. Working with large-scale enterprise systems requires familiarity with IBM's data platforms and cloud services, as well as strong problem-solving skills. Collaborating closely with data scientists, analysts, and other engineers is essential for aligning data solutions with business needs. Staying current with IBM's evolving technologies and participating in ongoing training can help address these challenges effectively.

What is the difference between Full Time Ibm Data Engineer vs Data Analyst?

AspectFull Time Ibm Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certifications, IBM-specific trainingBachelor's in Statistics, Data Analysis, or related field; certifications like Microsoft Data Analyst
Work EnvironmentData engineering teams, cloud platforms, enterprise IT environmentsBusiness units, reporting tools, data visualization platforms
Employer & Industry UsageTech companies, finance, healthcare using IBM technologiesRetail, marketing, finance across various industries

Full Time IBM Data Engineers focus on building and maintaining data pipelines, working with large-scale data systems, and implementing data architecture using IBM tools. Data Analysts interpret data, create reports, and support decision-making. While both roles work with data, Data Engineers handle infrastructure, whereas Data Analysts focus on insights and visualization.

What are the most commonly searched types of Ibm Data Engineer jobs in Seattle, WA?

The most popular types of Ibm Data Engineer jobs in Seattle, WA are:

What are popular job titles related to Full Time Ibm Data Engineer jobs in Seattle, WA?

For Full Time Ibm Data Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Full Time Ibm Data Engineer jobs in Seattle, WA look for?

The top searched job categories for Full Time Ibm Data Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Full Time Ibm Data Engineer jobs?

Cities near Seattle, WA with the most Full Time Ibm Data Engineer job openings:

Full Time Ibm Data Engineer jobs near you
Infographic showing various Full Time Ibm Data Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $147,621 per year, or $71 per hour.

Data Bricks Data Engineer

Tata Consultancy Service Limited

Seattle, WA • On-site

$120K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 26 days ago

Job description

Must Have Technical/Functional Skills
• Awareness of IBM Data Stage ETL/ELT data integration tool to understand existing code.
• Develop , Test , Deploy ,Optimize, and monitor large-scale data processing workloads in Azure Data Bricks ETL.
• Ensure and lead the efforts to review Legacy Data Stage legacy code and migrated Data bricks code to ensure functionality is not deviated
• Strong programming skills in Python and PySpark.
• Advanced proficiency writing SQL for analytics and ETL processes.
• Proven experience building and optimizing complex data pipelines in Azure.
• Hands-on experience with Azure Databricks: cluster management, job scheduling, workspace governance.
• Strong working knowledge of core Azure services: Storage Account, Synapse, Key Vault, VMSS, Function Apps, Web Apps, Log Analytics Workspace, service principals, and managed identities.
• Experience with container services (ACA, container instances) and containerized data workloads.
• Familiarity with Azure networking concepts and secure network integration for data platforms.
• Experience creating Azure infrastructure using ARM templates.
• Proficient with GitLab and Azure DevOps for CI/CD and source control workflows.
• Strong analytical, problem-solving, and communication skills; proven ability to work cross-functionally.
• Experience working in Agile teams and understanding of data governance frameworks.
• Hands-on experience provisioning Databricks resources with Terraform; ability to author and maintain Terraform templates and modules.
• Demonstrated experience implementing cluster autoscaling and autoscaling policies through Terraform.
• Experience creating reusable Terraform modules and implementing infrastructure-as-code best practices (module structure, state management, remote backends).
• Proven experience working on Databricks platform operations, including cluster configuration, job orchestration, and platform optimization.
• Experience configuring high-availability Databricks deployments and operating across multiple availability zones/regions.
• Familiarity with Metastore/Unity Catalog configuration and metadata governance in Databricks.
• Hands-on experience building data pipelines and ingestion workflows into medallion-layer architectures (bronze/silver/gold).
• Strong scripting skills (Python, Bash, or similar) and familiarity with CI/CD for Terraform and Databricks deployments.
• Strong troubleshooting, performance tuning, and cost optimization skills.
Responsibilities
• Design, develop, and maintain end-to-end data pipelines and ETL/ELT workflows using PySpark and Python.
• Ensure and lead the efforts to review Legacy Data Stage legacy code and migrated Data bricks code to ensure functionality is not deviated
• Implement, optimize, and monitor large-scale data processing workloads in Azure Databricks, including cluster configuration, autoscaling, and governance.
• Build and maintain data integration and orchestration solutions using Azure services to meet performance, availability, and security requirements.
• Collaborate with data consumers, thread authors/owners, and stakeholders to gather business requirements, prioritize needs, and translate analytical objectives into technical designs.
• Implement secure data access patterns using Azure Active Directory, Managed Identities, and service principals.
• Author Infrastructure-as-Code for Azure resources (ARM templates) and deploy consistent, repeatable environments.
• Configure and operate Azure components including Storage Account, Synapse, Key Vault, VMSS, Function Apps, Web Apps, Log Analytics Workspace, Azure Container Apps / container instances, and related services.
• Collaborate with networking and security teams to design and implement Azure networking for data solutions.
• Implement monitoring, alerting, and cost optimization for data workloads (Log Analytics, metrics, and dashboards).
• Use GitLab and Azure DevOps for source control, CI/CD pipelines, and release management.
• Follow Agile/Scrum practices and participate in sprint planning, standups, and retrospectives.
• Ensure solutions meet data governance, lineage, and compliance requirements.
• Operations Support and Oncall Support for Production Issues and Deployments.
Base Salary Range : $120,000 to $140,000 Per Annum
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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