Job Title : AWS Data Engineer IoT, ERP / MES, CRM & Generative AI Integration
Location : Remote / Onsite / Hybrid
Job Type : Full-Time
Experience Level : Mid to Senior Level
Industry : IoT, Industrial Automation, Enterprise Systems
Job Overview :
We are looking for a hands-on AWS Data Engineer with experience in IoT ecosystems, enterprise application integration, and emerging AI / ML capabilities. The ideal candidate will design and build modern data pipelines that process telemetry from IoT Core (MQTT) into Aurora PostgreSQL, while also integrating ERP / MES dumps, CRM field-service data, and cloud SaaS exports using tools like AWS Glue, AppFlow, and Lambda. Experience with LLM enablement and vector databases is a strong plus.
Key Responsibilities :
- Develop scalable data pipelines to handle data ingestion from :
1. IoT Core MQTT topics using AWS IoT Rules Aurora PostgreSQL for telemetry storage.
2. ERP / MES data dumps (e.g., SAP, Oracle Manufacturing) and CRM service exports (e.g., Salesforce, ServiceNow).
3. S3-based data uploads from field gateways or system exports.
Implement and maintain AWS Glue Jobs, AppFlow, and AWS Lambda functions to automate extraction, transformation, and loading (ETL / ELT).Create metadata-enriched, queryable datasets for use in analytics, dashboards, or feeding LLMs (Large Language Models) and vector databases for semantic search and intelligent applications.Design and optimize Aurora PostgreSQL schemas to support structured IoT telemetry, event logs, and traceability data.Integrate with SAP, Oracle, Salesforce, ServiceNow using AppFlow, REST APIs, or custom connectors.Enable real-time monitoring and alerting of IoT data pipelines and ensure high availability and resilience.Collaborate with AI / ML and data science teams to vectorize data using tools like Amazon OpenSearch, Pinecone, or FAISS, and build LLM pipelines for industrial search, chat, or recommendation use cases.Required Skills :
Strong hands-on expertise with AWS IoT Core, MQTT protocol, and IoT Rules Engine.Proficiency in Aurora PostgreSQL schema design, query tuning, and time-series handling.Proven experience with AWS Glue, Lambda, and AppFlow for orchestration and integration.Solid programming experience in Python or Node.js, especially for Lambda functions.Working knowledge of data lake architecture, S3, Glue Catalog, and Athena.Experience with ERP / MES system exports (e.g., SAP IDocs, BAPIs, Oracle DB dumps).Familiarity with Salesforce / ServiceNow APIs or AppFlow connectors.Exposure to LLM frameworks (LangChain, Bedrock, etc.) and vector databases (OpenSearch, Pinecone, etc.).Experience with CI / CD, Terraform / CloudFormation, and monitoring tools (e.g., CloudWatch, Prometheus).Preferred Qualifications :
AWS Certifications (e.g., AWS Certified Data Analytics, AWS Certified Machine Learning, Solutions Architect).Experience working in smart factory, industrial IoT, or connected device ecosystems.Exposure to Kafka or Kinesis for streaming pipeline implementations.Understanding of data governance, data lineage, and compliance standards.(ref : hirist.tech)
