Torchora
Back to Home

Key Responsibilities and Required Skills for Integration Assistant

💰 $55,000 - $85,000

IntegrationITOperationsCustomer Success

🎯 Role Definition

We are hiring an Integration Assistant to partner with product, engineering, and customer success teams to deliver reliable, repeatable integrations. This role focuses on end‑to‑end integration lifecycle activities including requirements gathering, data mapping, connector configuration, testing, issue triage, and documentation. The Integration Assistant plays a hands‑on role with APIs, iPaaS platforms, ETL patterns, and monitoring tools to ensure successful go‑lives and long‑term operational stability.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Integration Specialist / Integration Coordinator
  • Technical Support Engineer with API exposure
  • Junior Data Analyst or Junior Implementation Consultant

Advancement To:

  • Integration Specialist / Integration Engineer
  • Implementation Manager / Solutions Engineer
  • Middleware Developer or iPaaS Engineer

Lateral Moves:

  • Customer Success Manager (technical)
  • Product Operations or Technical Program Manager

Core Responsibilities

Primary Functions

  • Serve as the primary technical contact for assigned integration projects, gathering integration requirements, documenting data flows, and defining acceptance criteria with stakeholders and external partners.
  • Design and implement integrations using RESTful APIs, webhooks, JSON/XML payloads, and common authentication schemes (OAuth 2.0, API keys), ensuring secure and reliable data exchange.
  • Configure and maintain connectors in iPaaS and middleware platforms (e.g., Mulesoft, Dell Boomi, Workato, Zapier) and custom integration scripts to automate data synchronization between SaaS and on‑prem systems.
  • Create detailed data mappings, transformation rules, and field‑level reconciliation logic to align source and target schemas and ensure data integrity across systems.
  • Build, execute, and document integration test plans including unit tests, integration tests, and end‑to‑end validation to verify functionality and performance prior to deployment.
  • Troubleshoot and resolve integration issues across the stack by analyzing logs, replaying messages, and tracing API calls using tools like Postman, cURL, Splunk, or ELK.
  • Monitor integration health and SLA compliance, set up alerting/observability for failures, and respond to incidents to minimize downtime and data loss.
  • Coordinate and run customer onboarding activities, runbooks, and technical enablement sessions to accelerate client adoption of integrations.
  • Maintain and update technical integration documentation, runbooks, onboarding guides, and change logs in Confluence, Git, or other documentation systems.
  • Assist development teams by reproducing integration defects, creating reproducible test cases, and providing well‑scoped tickets with logs and steps to reproduce.
  • Execute ETL/ELT transformations and light data engineering tasks using SQL, Python, or scripting to prepare datasets for integrations when required.
  • Validate data migrations and cutovers, design rollback strategies, and support go‑live activities including smoke tests and post‑deployment verification.
  • Work with product and engineering to identify recurring integration patterns and help build reusable templates, connector libraries, and best practices.
  • Ensure compliance with data privacy and security policies during integration design, including PII handling, encryption in transit and at rest, and secure credential storage.
  • Support API versioning, backwards compatibility checks, and change management processes to reduce customer disruption during API updates.
  • Provide first‑line support for operational escalations, triage incoming integration issues from ticketing systems (JIRA, Zendesk), and communicate status updates to stakeholders.
  • Participate in sprint planning, backlog grooming, and cross‑functional standups to align integration work with product releases and customer milestones.
  • Collaborate with QA and automation engineers to introduce automated integration testing and regression suites to reduce manual test effort.
  • Analyze integration metrics (throughput, latency, error rates) and recommend performance optimizations or architectural changes to improve scalability.
  • Conduct vendor and third‑party connector evaluations, proof‑of‑concepts, and small pilot integrations to validate feasibility and TCO before wide adoption.
  • Assist in building onboarding templates and PS (professional services) scopes, estimating effort for complex integrations and producing clear statements of work.
  • Provide training and mentorship to junior integration staff and internal teams on connector configuration, API usage patterns, and common troubleshooting techniques.
  • Maintain a backlog of technical debt related to integration connectors and prioritize fixes that reduce operational toil and improve reliability.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.

Required Skills & Competencies

Hard Skills (Technical)

  • RESTful API integration and troubleshooting (GET, POST, PUT, DELETE, status codes).
  • Experience with JSON, XML, data serialization, and transformation patterns (XSLT, mapping tools).
  • Hands‑on experience with iPaaS or middleware platforms (e.g., Mulesoft, Dell Boomi, Workato, Zapier, Tray.io).
  • Proficiency in SQL for data validation, reconciliation, and ad‑hoc queries across systems.
  • Familiarity with authentication schemes and security best practices: OAuth2, JWT, API keys, TLS.
  • Practical knowledge of webhooks, polling strategies, and delta sync patterns for near‑real‑time integrations.
  • Exposure to scripting languages like Python, Bash, or Node.js for lightweight automation and ETL tasks.
  • Experience with monitoring and logging tools (Datadog, Splunk, ELK, CloudWatch) and setting alerts for integration failures.
  • Ability to use API testing and debugging tools (Postman, Insomnia, cURL) and read HTTP traces.
  • Knowledge of data privacy/regulatory requirements (GDPR, CCPA) and secure credential handling.
  • Familiarity with CI/CD basics and release processes for integration deployments.
  • Experience with ticketing and collaboration tools (JIRA, Zendesk, Confluence, Git).
  • Understanding of message queuing, SFTP, and file‑based integrations where applicable (FTP, SFTP, S3).
  • Data modeling fundamentals and experience creating data mapping documents and ER diagrams.

Soft Skills

  • Strong verbal and written communication tailored to technical and non‑technical audiences.
  • Excellent organization and time management: manage multiple concurrent integrations and customer priorities.
  • Problem‑solving mindset with a methodical approach to root cause analysis and remediation.
  • Customer‑facing skills: patient, empathetic, and able to explain technical tradeoffs clearly.
  • Collaborative team player comfortable working in cross‑functional, agile environments.
  • Attention to detail, especially when validating data mappings and edge case behaviors.
  • Proactive ownership and a bias for action to drive integrations to completion.
  • Ability to learn new platforms and adapt quickly to evolving product ecosystems.
  • Stakeholder management and expectation setting during complex or long‑running projects.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Information Technology, Computer Science, Information Systems, or equivalent practical experience.

Preferred Education:

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, or related field.
  • Certifications in integration platforms or cloud solutions (e.g., Mulesoft Certified Developer, Dell Boomi Associate, AWS Certified Cloud Practitioner).

Relevant Fields of Study:

  • Computer Science
  • Information Systems
  • Software Engineering
  • Data Analytics / Data Engineering

Experience Requirements

Typical Experience Range:

  • 1–4 years of relevant experience in integrations, APIs, or technical support focusing on system connectivity.

Preferred:

  • 2–5+ years working with SaaS integrations, iPaaS/middleware, API design and troubleshooting, and cross‑functional implementation projects.
Explore More Careers