Data Engineer

The ideal candidate will build scalable data platforms, develop cloud-native solutions, modernize enterprise databases, and deliver AI-powered applications using modern GenAI frameworks.

Mandatory Technical Skills

Python & Advanced SQL ETL/ELT & Data Pipeline Development AWS: RDS, S3, Glue, Lambda, Redshift, Bedrock Google Cloud Platform: BigQuery, Cloud SQL, Dataflow, Pub/Sub, Vertex AI Databases: Oracle, PostgreSQL, Couchbase Apache Spark, Kafka & Airflow REST APIs & Microservices Batch, Streaming & Real-Time Data Processing Docker, Git, CI/CD & Automation

GenAI / Agentic AI Skills

Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) LangChain & LangGraph CrewAI & AutoGen Agentic AI Architecture Vector Databases: Pinecone, FAISS, Chroma, pgvector AWS Bedrock & Google Vertex AI

Key Responsibilities

Design and develop scalable, cloud-native data engineering solutions.

Build and optimize batch, streaming, and real-time data pipelines.

Develop Python-based ETL/ELT workflows and microservices.

Design, migrate, and optimize Oracle, PostgreSQL, and Couchbase databases.

Implement GenAI-powered applications using LLMs, RAG, and Agentic AI frameworks.

Develop secure and scalable integrations across AWS and Google Cloud Platform.

Implement CI/CD, monitoring, automated testing, and data governance best practices.

We are looking for a highly skilled Senior Data Engineer with strong hands-on 10years experience in Python, SQL, AWS, Google Cloud Platform, database engineering, and Generative AI technologies., A hands-on, full-stack Data Engineer capable of delivering end-to-end solutions across data engineering, database modernization, cloud platforms, and GenAI-powered applications.