Job
Description
MuleSoft Integrations Design and configure Scheduler flows for time-triggered data synchronization Build time zone-aware, dynamic scheduler jobs using properties-based configuration Implement chained flows calling multiple downstream systems Monitor and audit scheduled runs for debugging and traceability Webhooks & Event-Driven Integrations Configure public-facing HTTP Listener endpoints with robust security and validations Handle webhook payloads asynchronously with deduplication and queuing logic Parse and validate headers, content types, and payload signatures Data Transformation Use DataWeave to transform data between JSON, XML, CSV, Java objects Handle complex nested mappings and reusable transformation functions Batch Processing Develop scalable batch jobs for file and data processing Integrate batch processing flows with cloud storage systems Connector Integrations Utilize connectors for AWS SQS, MongoDB, PostgreSQL, Airtable, and Slack Build resilient integrations with logging, retries, and monitoring using Anypoint Monitoring or Datadog Write custom loggers and error-handling strategies Technical Environment & Tools Anypoint Platform Studio, API Manager, Runtime Manager, Exchange DataWeave, MUnit, Postman, CloudHub, AWS MongoDB: Compass, Shell, Robo 3T PostgreSQL: pgAdmin, DBeaver, psql Airtable: REST API, JavaScript, OAuth Required Skills & Experience 3+ years of hands-on MuleSoft development experience Strong experience with Scheduler jobs, batch processing, webhooks, and data transformations Proficiency in designing and integrating with MongoDB, PostgreSQL, and REST APIs Strong SQL, JSON, XML transformation skills Ability to build and scale integrations using MuleSoft connectors Nice to Have Experience with MongoDB aggregation pipelines and ETL workflows Integration experience with Airtable (views, automations, REST API, scripting) Familiarity with OAuth, rate limiting, and building real-time sync with databases
