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Integration & Data Movement Engineer

(Enterprise Integrations & Data Flow Enablement)

Mustang Cat is actively seeking a highly skilled Integration & Data Movement Engineer to design, implement, and operate reliable data flows between enterprise platforms. This role is responsible for ensuring that data moves accurately, securely, and efficiently across systems such as CRM, ERP, finance, HR, analytics, and external partner platforms.

The Integration & Data Movement Engineer serves as both a hands-on builder and a technical steward of our integration landscape. This role works closely with application owners, data stakeholders, and platform engineers to understand system interactions, identify gaps or inefficiencies in data movement, and implement scalable, well-governed integration patterns. Success in this role requires a strong balance of engineering discipline, system thinking, and operational accountability.

Key Responsibilities:

Integration Enablement & Business Partnership

Partner with application owners and business stakeholders to understand how data flows between systems today and how those flows support operational and reporting needs.

Translate business and operational requirements into well-designed integrations that prioritize reliability, transparency, and maintainability.

Act as a technical advisor by connecting integration design decisions to downstream impacts on reporting, automation, and decision-making.

Support new initiatives and system changes by designing integrations that minimize disruption and reduce manual data handling.

Integration Architecture & Data Flow Design

Design and implement integrations across a diverse application ecosystem, including:

CRM, ERP, finance, HR, and marketing platforms
Internal data warehouses and analytics platforms
External vendors, partners, and third-party services

Select and apply appropriate integration patterns, including:

API-based (REST/SOAP) integrations
Event-driven and webhook-based integrations
Batch and scheduled data synchronization
File-based and ETL/ELT pipelines where appropriate

Ensure integrations are secure, resilient, and observable, with clear error handling and retry strategies.

Data Movement, Quality & Reliability

Build and maintain data pipelines that move data accurately and consistently across systems.

Implement validation, transformation, and enrichment logic to ensure data integrity and usability.

Monitor integration health, identify failures or latency issues, and proactively resolve root causes.

Partner with data and analytics teams to ensure integration outputs align with reporting and analytics requirements.

Standards, Documentation & Governance

Define and document integration standards and best practices, including:

API usage and authentication patterns
Error handling, logging, and monitoring expectations
Naming conventions and data contracts
Versioning and change management practices

Contribute to governance processes that ensure integrations remain scalable and understandable as the system landscape evolves.

Maintain clear technical documentation to support long-term ownership and operational continuity.

Implementation & Operational Support

Develop, test, and deploy integrations using approved tools and frameworks.

Support production operations by responding to integration incidents and participating in root cause analysis.

Continuously improve integration performance, reliability, and maintainability through refactoring and optimization.

Collaborate with infrastructure, security, and platform teams to ensure integrations align with enterprise standards.

Required Qualifications:

• 5–10+ years of experience designing and implementing system integrations and data pipelines.
• Strong hands-on experience with:
• REST and SOAP APIs
  Authentication and authorization (OAuth, API keys, certificates)
  Data transformation and mapping
  Error handling and retry mechanisms
• Experience working with integration platforms, middleware, or custom integration frameworks.
• Strong SQL skills and experience working with relational data models.
• Ability to understand complex system landscapes and reason about data flow dependencies.
• Strong communication skills, with the ability to explain integration behavior and issues to non-technical stakeholders.

Preferred Qualifications:

• Experience with cloud-native integration patterns and services (ie., Azure, AWS, GCP).
• Experience with data warehouses and analytics platforms (ie., Snowflake).
• Familiarity with message queues or event streaming technologies (ie., Kafka, Service Bus).
• Experience supporting integrations in regulated or security-conscious environments.
• Prior experience working in environments with multiple enterprise SaaS platforms.

What Success Looks Like:

Data moves reliably and predictably across systems with minimal manual intervention.

Integrations are well-documented, observable, and resilient to upstream or downstream changes.

Business teams trust the accuracy and timeliness of data flowing between platforms.

New systems and initiatives are onboarded efficiently with clean, repeatable integration patterns.

The integration landscape scales without becoming fragile or overly complex.