Job highlights

- 2+ years of experience in containerization and orchestration,including creating,deploying,and managing containers using Docker and Kubernetes

- 5-7 years of overall experience in Data Engineering,building scalable and production-grade data platforms

- 5-7 years of strong experience with ETL / ELT frameworks and data integration,including designing reliable and scalable data pipelines

Job Summary

Senior Data Engineer

Location: Bangalore

Company: kmartaustr

Requirements

- 5-7 years of overall experience in Data Engineering, building scalable and production-grade data platforms.

- 3+ years of hands-on experience with AWS services, including IAM, API Gateway, EC2, S3, and related cloud services.

- 2+ years of experience in containerization and orchestration, including creating, deploying, and managing containers using Docker and Kubernetes.

- 2+ years of experience building and managing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or equivalent.

- 2+ years of hands-on experience with Snowflake, including data warehousing, data modelling, performance optimization, and integration with ETL/ELT pipelines.

- 5-7 years of strong experience with ETL/ELT frameworks and data integration, including designing reliable and scalable data pipelines.

- 5-7 years of experience with Big Data technologies such as Apache Spark and Kafka,



including large-scale data processing and streaming workloads.

- Robust programming experience in Python, with working knowledge of Java or Scala for data engineering applications.

- AI / Generative AI experience: Exposure to integrating LLMs into enterprise applications and data platforms, including prompt engineering, embeddings, RAG (Retrieval-Augmented Generation), vector databases, and LLM APIs.

- Agentic AI: Understanding or hands-on experience building AI agents and agentic workflows, including tool/function calling, multi-step reasoning workflows, orchestration, and integration of agents with enterprise data sources and APIs.

- AI Data Engineering: Experience preparing and managing structured/unstructured datasets for AI/ML and GenAI workloads, including data ingestion, transformation, chunking, metadata management, embeddings, and data quality/governance.

- Good to have: Exposure to frameworks and platforms such as LangChain, LangGraph, LlamaIndex, Amazon Bedrock, or Azure OpenAI for developing enterprise GenAI or Agentic AI solutions.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr. Data Engineer (Bengaluru)
🏢 KAS Services
📍 Bengaluru