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Ibm Data Engineer Jobs (NOW HIRING)

S3 Staffing USA

Data Bricks Data Engineer

Plano, TX · On-site

$110K - $132K/yr

Data Bricks Data Engineer Location: Seattle, WA / Bellevue, WA / Everett, WA / Renton, WA ... of IBM Data Stage ETL/ELT data integration tool to understand existing code. Develop , Test ...

NAVA Software Solutions

Data Engineer - Azure

Weehawken, NJ · On-site

$124K - $149K/yr

Cloud Data Engineer/Strong in Azure Location - Weehawken NJ - Hybrid Type: FTE / Direct Hire We are ... You should have strong experience with MS SQL and be familiar with AWS DynamoDB and IBM DB2.

Texas State Library and Archives Commision

Data Engineer

$117K - $140K/yr

Implement best practices for data modeling to ensure efficient reporting in IBM Cognos Analytics ... Support Cognos report developers in structuring data efficiently to meet reporting needs. Implement ...

ComResource

Data Engineer

Cincinnati, OH

$109K - $131K/yr

ComResource is looking for a Data Engineer. We need someone to assist in calculating FDIC insurance ... Desired: * Experience with IBM DB2 and DataStage. * Familiarity with modern data tools like ...

Kanak Elite Services Inc

$109K - $130K/yr

Don't send Sr Level Developer * Bachelor's degree Desired ... IBM Cloud * Datastage * DB2 * watsonX.ai * Supply Chain WHAT YOU'LL DO * Automate data wrangling ...

EOG Resources, Inc.

Sr. Data Engineer

Houston, TX · On-site

$109K - $131K/yr

... IBM iseries platform and Oracle, including large data ingestion, replication, persistence ... Bachelor's Degree in Computer Science, Computer Engineering, Computer Information Systems ...

City of New York

Senior Data Engineer

Brooklyn, NY · On-site

$115K - $156K/yr

In this capacity, Data Engineer will: - Design and implement end-to-end ETL pipelines using IBM DataStage for legacy and modern data sources. - Develop and maintain source-to-target mappings (STTM ...

TMS

Data Engineer - Netezza & DataStage

Edison, NJ · On-site

Contract Job Summary We are seeking an experienced Data Engineer with strong expertise in IBM Netezza and IBM DataStage , along with hands-on or working experience in Snowflake and Databricks . The ...

EOG Resources, Inc.

Sr. Data Engineer

Houston, TX · On-site

$109K - $131K/yr

... IBM iseries platform and Oracle, including large data ingestion, replication, persistence ... Bachelor's Degree in Computer Science, Computer Engineering, Computer Information Systems ...

NAVA Software Solutions

Big Data Engineer

Atlanta, GA · On-site

$53.50 - $71/hr

Big Data Engineer Location: Atlanta GA - Hybrid Duration: 12 months The successful candidate must ... Strong knowledge of Messaging Platforms like Kafka, Amazon MSK & TIBCO EMS or IBM MQ Series

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IBM Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do ibm data engineer jobs pay per year?

As of Jul 18, 2026, the average yearly pay for ibm data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

Can I make 200K as a data engineer?

Senior IBM Data Engineers with extensive experience, advanced skills in cloud platforms, big data tools, and certifications can potentially earn salaries around or above $200,000 annually, especially in high-cost-of-living areas. Entry-level or mid-level data engineers typically earn less, with salaries increasing based on expertise, location, and industry demand.

What is an IBM Data Engineer job?

An IBM Data Engineer is responsible for designing, building, and managing data pipelines and architectures to support data-driven decision-making. They work with data integration, ETL processes, cloud platforms, and big data technologies to ensure efficient data flow. IBM Data Engineers collaborate with data scientists, analysts, and business stakeholders to optimize data accessibility and performance. Their role often involves using IBM technologies such as IBM Cloud, Db2, and Watson Studio to implement scalable data solutions. Strong skills in SQL, Python, and data modeling are essential for success in this role.

What are typical day-to-day tasks for an IBM Data Engineer?

As an IBM Data Engineer, your daily responsibilities often include designing and building data pipelines, integrating data from various sources, and ensuring the reliability and quality of data architecture. You may work closely with data scientists, analysts, and business stakeholders to understand requirements and optimize data workflows. Regular tasks involve maintaining and troubleshooting ETL processes, performing data validation, and documenting solutions. Collaboration within agile teams is common, and staying updated on IBM technologies and best practices is critical for ongoing success.

Is IBM a good company for data engineers?

IBM is a well-established technology company that employs data engineers to work on large-scale data projects, often involving cloud platforms, AI, and analytics tools. The company offers opportunities for skill development in areas like data pipelines, SQL, and cloud certifications, making it a reputable employer for data engineering roles.

How much does a data engineer at IBM make?

A data engineer at IBM typically earns between $90,000 and $130,000 annually, depending on experience, location, and skill level. Salaries can vary based on certifications, such as cloud or big data tools, and the complexity of projects handled.

What are the key skills and qualifications needed to thrive in the Ibm Data Engineer position, and why are they important?

To thrive as an IBM Data Engineer, you need strong proficiency in data modeling, ETL processes, and SQL or Python programming, typically supported by a bachelor’s degree in computer science, engineering, or a related field. Expertise with IBM data tools like IBM DataStage, IBM Cloud Pak for Data, and knowledge of big data platforms such as Hadoop or Spark, along with relevant IBM certifications, are highly valuable. Effective problem-solving abilities, attention to detail, and collaboration skills help you excel in cross-functional teams and adapt to evolving project needs. These skills and qualities are essential for designing robust data pipelines and delivering reliable, enterprise-level data solutions.

Is it hard to get hired by IBM?

Getting hired as an IBM Data Engineer can be competitive, requiring strong technical skills in data processing, programming, and cloud platforms like IBM Cloud or AWS. Candidates often need relevant experience, certifications, and a solid understanding of data architecture to improve their chances.
More about IBM Data Engineer jobs
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IBM Data Engineer jobs near you
Infographic showing various Ibm Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Bricks Data Engineer

S3 Staffing USA

Plano, TX • On-site

$110K - $132K/yr

Other

Posted 9 hours ago

Job description

Title: Data Bricks Data Engineer Location: Seattle, WA / Bellevue, WA / Everett, WA / Renton, WA / Richardson, TX / Plano, TX / Dallas, TX / St. Louis, MO / Charleston, SC / Arlington, VA/Onsite

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.


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