Data Engineer-GenAI

Auxo AI; Gurugram District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

AuxoAI is seeking a Senior GenAI Data Engineer to design production-grade data pipelines and end-to-end solutions. You will leverage GenAI tools to boost productivity and shape best practices across complex data environments.

The role requires 4+ years in data engineering, with expertise in batch/streaming pipelines, data modeling, SQL, Python, and Spark. GCP services and AI coding tools are central to daily work.

Qualifications

• 4+ years of data engineering experience
• End-to-end pipeline development (batch and streaming)
• Data modeling (dimensional, Data Vault, OBT)
• SQL (Advanced) and Python (Advanced)
• Apache Spark for large-scale processing
• AI coding tools to boost productivity
• GCP services: BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI
• Familiarity with Databricks, Delta Lake or Apache Iceberg
• GCP Professional Data Engineer certification is a plus

Responsibilities

• Architect and develop end-to-end data pipelines—from ingestion to consumption
• Lead solutioning and integration for batch and streaming data workflows
• Use AI coding tools (Copilot, Claude, Gemini) to accelerate coding
• Implement data quality, testing, lineage, and governance frameworks
• Drive best practices for pipeline performance, reusability, and scalability
• Mentor junior engineers and contribute to capability building within the data team

Skills

Data engineering

Python

SQL

Apache Spark

Generative AI

Tools

BigQuery

Dataflow

Cloud Composer

Pub/Sub

Dataproc

Vertex AI

Databricks

Delta Lake

Apache Iceberg

GitHub Copilot

Claude

Gemini

Job description

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Experience: 4+ Years

Role Summary

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption
• Lead solutioning and integration for complex data workflows (batch and streaming)
• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging
• Implement robust data quality, testing, lineage, and governance frameworks
• Drive best practices across pipeline performance, reusability, and scalability
• Mentor junior engineers and contribute to capability building within the data team

Requirement

• 4+ years of experience in data engineering, with expertise in:
• End-to-end pipeline development (batch and streaming)
• Data modeling (dimensional, Data Vault, OBT)
• ETL/ELT design patterns, performance tuning, and optimization
• SQL (Advanced) and Python (Advanced)
• Apache Spark for large-scale data processing
• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality
• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows
• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI
• Exposure to finance or sales data domains
• Familiarity with Databricks, Delta Lake, or Apache Iceberg
• GCP Professional Data Engineer certification is a plus

Skills:- Data engineering, Python, Apache Spark and Generative AI