Data Engineer

For more than three decades, Aeris has been a trusted cellular IoT leader enabling the biggest IoT programs and opportunities across Automotive, Utilities and Energy, Fleet Management and Logistics, Medical Devices, and Manufacturing. Our IoT technology expertise serves a global ecosystem of 7,000 enterprise customers and 30 mobile network operator partners, and 90 million IoT devices across the world. Aeris powers today’s connected smart world with innovative technologies and borderless connectivity that simplify management, enhance security, optimize performance, and drive growth.

Experience: 4+ Years

Role Summary

Build and maintain the enterprise data lake, design ETL pipelines, develop ML models for forecasting, and create AI agents/MCP integrations using LLM APIs.

Required Skills

• Python ETL — Pandas, NumPy, data modelling, API integrations
• SQL — Complex queries, schema design, performance tuning
• GCP — BigQuery, Cloud Storage, CloudRun, Secret Manager
• Data Lake Design — Ingestion from ERP/CRM systems (NetSuite, Salesforce), schema evolution, data quality
• REST API — Development and consumption (OAuth, webhooks)
• Git & CI/CD — Version control and deployment basics

• AI Agent Development — Tool-calling agents, MCP servers, LLM APIs (Claude, Gemini, OpenAI)
• Machine Learning — Time series forecasting, predictive modelling (Prophet, XGBoost, SARIMAX)
• BI Tools — Qlik or Looker
• Orchestration — Cloud Scheduler, Airflow, or cron-based job pipelines

• Build and maintain data lake on BigQuery — ingestion, transformation, scheduling
• Design and implement ETL pipelines (Python) across banking, ERP, and CRM sources
• Experiment with and deploy ML models for cash forecasting and business predictions
• Develop AI agents and MCP tool integrations using LLM APIs
• Ensure data quality, monitoring, and alerting across pipelines