Integration Engineer (Mulesoft / Any Integration tool)

About Reveleer Reveleer delivers a unified platform spanning risk adjustment, quality improvement, clinical intelligence, and member management for health plans and provider organizations navigating the complexity of value-based care. Trusted by 80+ customer organizations nationwide, the platform integrates data, analytics, and intelligent workflow automation into one governed system designed to support traceable documentation across diagnoses, quality measures, and submissions. With regulatory expertise and transparent, human-in-the-loop AI at its core, Reveleer supports organizations working to advance care quality, strengthen documentation integrity, and sustain the operational readiness needed to navigate audits with confidence. What are we looking for? We are looking for a Data Engineering – Integration Engineer to primarily support and continuously improve our existing MuleSoft-based integration and data onboarding ecosystem. This role is responsible for production support of live integrations and data pipelines — monitoring, troubleshooting, incident resolution, and data validation — along with ongoing enhancements, automation, and dashboard development. The ideal candidate has hands-on experience supporting MuleSoft integrations in production, strong SQL and AWS S3 troubleshooting skills, and is comfortable working in a 24x7 rotational shift environment, preferably within healthcare or other regulated domains. Responsibilities Production Support & Operations Provide 24x7 rotational on-call support for existing MuleSoft integrations, APIs, and data pipelines, ensuring timely detection and resolution of production issues. Triage, investigate, and resolve production incidents related to integration failures, file processing errors, and data mismatches; perform root-cause analysis and document post-incident reports. Troubleshoot data issues using SQL — querying, validation, and reconciliation across relational databases during live incidents. Monitor and troubleshoot AWS S3 bucket activity — file arrival delays, permission issues, failed/stuck files, reprocessing, and lifecycle configuration. Monitor integrations and pipelines using Anypoint Monitoring, CloudWatch, or equivalent APM/logging tools; respond to alerts proactively. Maintain and contribute to a knowledge base / runbooks documenting recurring issues, root causes, and resolution steps for faster future troubleshooting. Manage support tickets end-to-end (triage, prioritization, resolution, closure) against defined SLAs using Jira or similar tools. Support EDI transaction processing in production — investigating rejections, acknowledgment mismatches, and HIPAA transaction errors. Work with connector-level resilience (timeouts, retries, circuit breakers, dead-letter handling) to diagnose and fix integration failures. Troubleshoot messaging/queue-based issues — message backlogs, poison messages, DLQ handling — across SQS, Anypoint MQ, and/or Kafka/JMS. Perform data quality checks, audits, and reconciliation across large datasets, including scheduled/batch jobs (e.g., Vcron, Quartz, cron-based, or cloud-native schedulers). Development & Enhancement Enhance and optimize existing MuleSoft integrations and DataWeave transformations for performance, reliability, and maintainability. Build automation scripts and utilities (Node.js/TypeScript, Python) to reduce manual effort in support and operational workflows. Design and build dashboards for pipeline health, SLA tracking, and operational visibility. Contribute to new integration or data onboarding requirements as they arise, following existing API-led and DataWeave patterns. Apply MuleSoft best practices (centralized error handling, flow modularization, reusable components) when modifying or extending existing flows. Participate in CI/CD pipeline maintenance (Bitbucket Pipelines, Maven-based build/release) for environment promotion and deployments. Collaborate with product, QA, and data teams to translate support learnings and business requirements into pipeline and integration improvements. Required Education and Experience Production Support Proven experience in a production/L2–L3 support role for integration, API, or data platforms, including 24x7 rotational on-call coverage. Strong hands-on troubleshooting skills using SQL for data validation, reconciliation, and issue diagnosis in live environments. Experience working with AWS S3 — bucket structure, permissions, file lifecycle, and troubleshooting failed or delayed file transfers. Experience with incident/ticket management tools (Jira, ServiceNow, or similar) and adherence to SLA-driven support processes. Experience maintaining or using a knowledge base/runbook system to document and resolve recurring production issues. Experience with monitoring/alerting/observability tools (Anypoint Monitoring, CloudWatch, Splunk, Datadog, New Relic, or similar). MuleSoft & Integration Solid experience supporting and troubleshooting MuleSoft Anypoint Platform (Mule 4.x) applications deployed on CloudHub 2.0. Working knowledge of API-led connectivity, RAML/OAS specifications, and Anypoint Exchange — sufficient to understand and modify existing designs. Proficiency in DataWeave 2.0 for troubleshooting and enhancing existing data transformations across JSON, XML, CSV, and EDI payloads. Experience with MuleSoft connectors (Database, HTTP/HTTPS, SFTP, File, SQS) and diagnosing connector-level failures. Familiarity with API Manager and Runtime Manager for monitoring policy enforcement, API instance health, and troubleshooting runtime issues. Exposure to Anypoint Private Space, Runtime Fabric, or hybrid deployments is a plus. Messaging & Event-Driven Architecture Hands-on experience troubleshooting message queue and event streaming issues — Amazon SQS, Anypoint MQ, Kafka, or JMS/ActiveMQ. Understanding of messaging patterns: pub/sub, message ordering/deduplication, idempotent processing, and dead-letter queue (DLQ) handling. Experience diagnosing message backlogs, throughput bottlenecks, and consumer scaling issues in production. Backend & Data Engineering Strong experience in Node.js and TypeScript for backend services, automation scripts, and data-processing utilities. Strong SQL skills across relational databases for validation, reconciliation, and data quality checks. Experience with ETL/ELT workflows and multi-stage data pipeline troubleshooting. Comfortable handling multiple file formats: CSV, TXT, PSV, and other delimited/structured formats. DevOps, CI/CD & Cloud Deployment Familiarity with CI/CD pipelines (Bitbucket Pipelines or similar) for build, test, and deployment support. Working knowledge of Git branching/release strategies and Bitbucket for source control and PR-based reviews. Experience operating workloads on AWS (S3, and general familiarity with compute, storage, networking, IAM); Azure/GCP experience is a plus. Understanding of environment strategy (Dev → QA → Stage → Prod) and rollback procedures. EDI & HIPAA / Healthcare Compliance Working knowledge of HIPAA-mandated X12 EDI transaction sets from a support/troubleshooting perspective. Ability to investigate and resolve EDI transaction failures, acknowledgment mismatches, and companion guide conformance issues. Working knowledge of HIPAA Privacy and Security Rule requirements: minimum necessary access, audit logging, and secure handling of PHI/PII. Familiarity with payer/provider data exchange concepts (eligibility, claims, risk adjustment, HEDIS/Stars) is a plus. AI-Assisted & Model-Driven Development Working experience with AI/LLM tools (OpenAI, Anthropic, AWS Bedrock, or similar) for troubleshooting assistance, documentation generation, or automation scripting. Comfortable using AI coding tools to accelerate scripting/automation work, with the judgment to review and validate AI-generated output before use. Working knowledge of Python for scripting and automation tasks is a plus. Hands-on experience performing data analysis using AI/LLM tools — using AI-assisted workflows to explore datasets, summarize trends, and generate insights that support production support and data quality decisions. Experience building and working with AI-driven bots and conversational/automation agents, including hands-on development with Claude-based bots and tooling for support automation and internal workflows. Additional Desired Skills Experience with Flatfile or similar data onboarding platforms. Familiarity with React + TypeScript for internal tooling/admin UIs is a plus. Understanding of data security fundamentals — key management, secrets rotation, secure coding practices. Prior exposure to building or maintaining bots for support, monitoring, or workflow automation is a plus. Soft Skills Strong ownership and accountability. Excellent communication and cross-team collaboration skills. High attention to detail, especially around data accuracy and quality. Ability to work independently in a fast-paced environment. Mentorship mindset and willingness to support and upskill team members. Qualifications Bachelor’s degree in Computer Science, Information Technology, or a related field — B.Tech/B.E. (CS/IT or related), B.Sc. Computer Science, B.Sc. IT, or MCA. 3–5 years of relevant experience in integration production support and backend/data engineering. Proven experience supporting live integration or data pipeline systems in production environments, including incident resolution and SQL-based troubleshooting. Experience working in Agile/Scrum delivery environments, using tools such as Jira for sprint planning, backlog grooming, and task/issue tracking, and Bitbucket (repos + pipelines) for source control, pull-request reviews, and CI/CD. Note