AWS Data Engineer

Job Title: AWS Data Engineer – IoT, ERP/MES, CRM & Generative AI Integration

Location: [Remote / Onsite / Hybrid – Specify]
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:
• IoT Core MQTT topics using AWS IoT Rules ➜ Aurora PostgreSQL for telemetry storage.
• ERP/MES data dumps (e.g., SAP, Oracle Manufacturing) and CRM service exports (e.g., Salesforce, ServiceNow).
• 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.

Job Type: Full-time

Pay: ₹1,300,000.00 - ₹2,000,000.00 per year

Experience:

• Aws Data Engineer: 6 years (Required)
• IOT industry: 2 years (Required)
• ERM data Exports: 4 years (Required)
• CRM Data Dumps: 4 years (Required)

Work Location: In person