Data Engineer

Aeris; Gurugram District; On-site; INR 1,400,000 - 2,200,000; Full time

Job summary

Aeris is seeking an experienced data engineer to build and maintain an enterprise data lake on BigQuery, design robust ETL pipelines, and develop ML models for forecasting. This role emphasizes scalable automation, data quality, and AI agent integrations via LLM APIs.

You will work with Python, SQL, and GCP, ingest ERP/CRM data (NetSuite, Salesforce), implement orchestration with Airflow, and collaborate across teams to deliver reliable data products.

Qualifications

• 4+ years in data engineering or related field.
• Experience building data lakes and ETL pipelines.
• Proficiency in Python, SQL, and GCP.
• Knowledge of data quality monitoring and orchestration.
• Experience with ERP/CRM data sources like NetSuite or Salesforce.

Responsibilities

• Build and maintain data lake on BigQuery.
• Design and implement ETL pipelines across banking, ERP, and CRM sources.
• Experiment with and deploy ML models for forecasting.
• Develop AI agents and MCP tool integrations using LLM APIs.
• Ensure data quality, monitoring, and alerting across pipelines.

Skills

Python

ETL

SQL

GCP

Data Lakes

REST APIs

Git

CI/CD

Education

4+ years in Data Engineering or related field

Tools

BigQuery

Cloud Storage

CloudRun

Secret Manager

Airflow

Job description

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

Preferred Skills:

• 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

Key Responsibilities:

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