DataPower Platform Engineer

CoSourcing Partners Inc.; Dallas, San Antonio (TX, TX); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Global Professional Services Organization seeks a DataPower Platform Engineer to own and operate IBM API Connect and DataPower environments in a hybrid setup in Dallas or San Antonio. The role requires hands-on administration, platform configuration, and proactive incident resolution in a client-facing professional services setting.

The engineer will work with Linux, CI/CD processes, and deployment automation to ensure API reliability and platform stability across environments, partnering with

Qualifications

• Hands-on IBM API Connect administration and platform configuration.
• Hands-on IBM DataPower operational experience.
• Experience with Linux environments and CI/CD processes.
• Ability to work with client stakeholders and delivery teams.

Responsibilities

• Establish ownership of IBM API Connect and DataPower environments.
• Improve platform reliability and production stability.
• Strengthen API deployment and CI/CD practices.
• Enhance monitoring, documentation, and knowledge transfer.

Skills

Analytical thinking

Problem solving

Communication

Stakeholder collaboration

Tools

IBM API Connect

IBM DataPower

CI/CD tooling

Linux

Job description

Position: DataPower Platform Engineer

Company: Global Professional Services Organization

Client Industry: Transportation

Location: Dallas, TX or San Antonio, TX

Work Arrangement: Hybrid – Onsite at Client HQ 2 Days per Week

Employment Type: W2 Contract-to-Hire

Engagement Requirement: W2 candidates only; C2C is not permitted

Overview

The IBM API Connect / DataPower Platform Engineer will provide hands‑on engineering, administration, configuration, deployment, and production support for enterprise API infrastructure supporting a major Transportation client. The primary responsibility is maintaining a stable, secure, and reliable IBM API Connect and IBM DataPower environment while enabling technical teams to deploy and operate APIs effectively. This is a hands‑on platform engineering position rather than an API development‑only or architecture‑only role. The successful candidate must be capable of working directly within IBM API Connect and DataPower environments to configure platform components, support deployments, troubleshoot failures, monitor platform health, investigate production incidents, and resolve issues affecting API availability or performance. The engineer will also work with Linux environments and CI/CD processes supporting platform operations and API deployment. Because this position operates within a Global Professional Services organization, the individual must combine strong technical execution with the ability to work effectively with client stakeholders, engineering teams, infrastructure resources, and other delivery partners.

Purpose

Take direct ownership of API infrastructure that enables critical applications and services to communicate reliably across a major Transportation enterprise. Your work will directly influence API availability, deployment reliability, production stability, and the ability of engineering teams to deliver technology capabilities to the business. Expand expertise across enterprise API platform engineering, IBM API Connect, DataPower, Linux, monitoring, deployment automation, troubleshooting, and CI/CD while operating within a large professional services and client environment. The contract‑to‑hire structure provides an opportunity to demonstrate technical leadership and potentially transition into a longer‑term position. This opportunity is well suited to an engineer who enjoys hands‑on platform ownership and solving difficult production problems. Rather than simply developing individual APIs, the engineer will help ensure that the underlying API platform is configured correctly, monitored effectively, deployed consistently, and capable of supporting enterprise workloads reliably.

Candidate Requirements

Hands‑on IBM API Connect administration and platform configuration experience is required. The candidate should be able to describe specific environments they have personally administered, the platform activities they owned, production problems they encountered, and how they diagnosed and resolved those problems. Hands‑on IBM DataPower operational experience is also required.

Objectives

• 1. Establish Operational Ownership of IBM API Connect and DataPower. Within the first 30–60 days, develop a detailed understanding of the client's IBM API Connect and DataPower environments, including platform configuration, runtime components, deployment processes, integrations, monitoring, operational dependencies, and known issues. Assume increasing responsibility for day-to-day platform administration and independently resolve routine-to-moderately complex operational problems while appropriately escalating issues requiring broader support. Document critical gaps or risks discovered during the assessment and prioritize corrective actions with the responsible technical teams. Success will be measured by increasing independence, effective platform administration, timely problem resolution, and stakeholder confidence in the engineer's ability to support the environment.

• 2. Improve API Platform Reliability and Production Stability. Within the first 90–180 days, proactively monitor IBM API Connect and DataPower platform health, identify recurring or high‑impact operational problems, and implement or recommend improvements that increase platform reliability and supportability. Troubleshoot API failures, platform issues, connectivity problems, configuration errors, deployment failures, and other production incidents by using logs, monitoring information, Linux tools, platform diagnostics, and structured root‑cause analysis. Work across appropriate technical teams when incidents involve dependencies outside the API platform. Success will be measured by improved platform stability, timely incident resolution, reduction of recurring issues, and increased visibility into platform health. AI‑assisted log or incident analysis may be used where permitted, with technical conclusions independently verified before production changes are made.

• 3. Establish Reliable API Deployment and CI/CD Practices. During the first six months, strengthen the processes used to configure, package, deploy, validate, and promote API‑related changes across environments. Work with CI/CD capabilities and engineering teams to reduce manual deployment risk, improve repeatability, and ensure changes to API Connect and DataPower can move through appropriate environments in a controlled manner. Troubleshoot deployment failures and identify opportunities to automate repetitive platform activities while maintaining appropriate controls and rollback capabilities. Success will be measured by reliable deployments, reduced manual intervention, faster resolution of deployment failures, and improved consistency across environments.

• 4. Strengthen Platform Monitoring, Supportability, and Knowledge Transfer. Throughout the engagement, improve monitoring, operational procedures, troubleshooting documentation, deployment knowledge, and support practices for IBM API Connect and DataPower. Identify gaps that create unnecessary dependence on individual resources and develop reusable procedures that allow the broader team to diagnose and resolve common platform issues more efficiently. Work collaboratively with client and professional services teams to share knowledge and improve long‑term operational readiness. Success will be measured by improved monitoring coverage, usable operational documentation, faster troubleshooting, reduced key‑person dependencies, and stronger overall platform support capability.

Subtasks

• 1. Assess the Existing API Platform Environment. During the first 30 days, review the IBM API Connect and DataPower environments to understand architecture, configuration, runtime components, Linux dependencies, deployments, monitoring, integrations, operational procedures, and known technical issues. Meet with client and professional services resources to understand current support expectations and priority concerns. Identify immediate operational risks and gaps requiring attention and establish an initial action plan. Success will be measured by a reliable current‑state assessment and agreement on priority platform activities.

• 2. Administer and Configure IBM API Connect. Beginning within the first 30–60 days, perform hands‑on IBM API Connect administration and platform configuration required to support stable API operations. Investigate configuration issues, support platform changes, assist API deployments, and troubleshoot problems affecting the ability of applications and services to use the API environment successfully. Follow appropriate change and production‑control procedures while maintaining sufficient documentation of significant modifications. Success will be measured by configuration accuracy, reliable platform operation, timely completion of assigned changes, and reduced configuration‑related incidents.

• 3. Operate and Troubleshoot IBM DataPower. Within the first 60–90 days, assume hands‑on responsibility for applicable DataPower operational activities and investigate issues involving API traffic, connectivity, configuration, deployment, or runtime behavior. Use DataPower diagnostics, logs, monitoring information, and related Linux or infrastructure information to determine root causes rather than treating symptoms alone. Coordinate with dependent teams when resolution requires changes outside DataPower. Success will be measured by accurate troubleshooting, timely incident resolution, and reduction in recurring DataPower‑related issues.

• 4. Monitor Platform Health and Resolve Production Issues. Throughout the engagement, actively monitor API Connect and DataPower environments and respond to platform alerts, failures, performance concerns, and service‑impacting incidents. Correlate monitoring data, logs, recent deployments, configuration changes, and system dependencies to identify likely root causes and appropriate corrective actions. Communicate significant incidents and resolution status clearly to client and technical stakeholders. Success will be measured by timely detection, reduced mean time to resolution, improved production stability, and fewer recurring incidents.

• 5. Support Deployments and CI/CD Automation. During the first six months, support and improve CI/CD processes associated with API and platform deployments, reducing unnecessary manual effort and increasing deployment repeatability. Troubleshoot failed deployments, identify environmental or configuration differences, and work with development and DevOps resources to strengthen promotion and validation processes. Ensure automation includes appropriate controls, error handling, validation, and recovery considerations. Success will be measured by improved deployment reliability, reduced manual intervention, and faster recovery from unsuccessful releases.

• 6. Improve Platform Operations and Client Support. Throughout the engagement, identify opportunities to improve platform configuration, monitoring, troubleshooting procedures, deployment practices, operational documentation, and knowledge sharing. Work directly with client stakeholders during the required two‑day‑per‑week onsite schedule in Dallas or San Antonio to understand operational concerns and accelerate resolution of technical issues when appropriate. Document recurring problems and effective solutions so that knowledge becomes reusable across the support organization. Success will be measured by improved operational efficiency, stronger client confidence, better documentation, and increased team capability.

• 7. Continuously Evaluate and Integrate AI to Improve Performance. Within the first 90–180 days, take ownership of identifying how AI and automation can support or enhance API platform engineering activities. Evaluate opportunities involving log analysis, incident correlation, configuration review, monitoring, deployment validation, CI/CD troubleshooting, documentation, and knowledge retrieval, and lead appropriate pilots where organizational and client policies permit. Validate AI‑generated technical conclusions against authoritative platform data and require human review before configuration or production changes are implemented. Success will be measured by demonstrable improvements in troubleshooting speed, operational efficiency, deployment quality, or knowledge accessibility without compromising security, accuracy, confidentiality, or production stability.