Job Summary

We are seeking a highly motivated and experienced Senior Data Engineer to join our Data Engineering team. The ideal candidate will have extensive experience designing and building scalable data pipelines using the AWS cloud ecosystem, with deep expertise in Snowflake, Python, and SQL. Experience with graph databases, vector databases, and AI-driven data platforms is highly desirable.

In this role, you will design and optimize modern data platforms that support analytics, machine learning, semantic search, Retrieval-Augmented Generation (RAG), and enterprise AI applications. You will work closely with cross-functional teams to deliver secure, scalable, and high-performance data solutions.

Key Responsibilities

- Design, develop, and maintain scalable data pipelines using AWS services such as S3, Glue, Lambda, Redshift, and EMR.
- Build, optimize, and maintain enterprise data warehouse solutions using Snowflake, including data modeling, query optimization, and performance tuning.
- Develop efficient, reusable, and maintainable data transformation workflows using Python and SQL.
- Collaborate with data scientists, analysts, architects, and business stakeholders to gather requirements and deliver scalable data solutions.
- Integrate vector databases with Large Language Model (LLM) applications and AI-driven workflows.
- Design and optimize graph and vector data architectures to support semantic search, Retrieval-Augmented Generation (RAG), and AI use cases.
- Monitor, troubleshoot, and optimize data pipelines for reliability, scalability, and performance.
- Ensure data quality, governance, security, and compliance across all stages of the data lifecycle.
- Participate in architecture reviews, code reviews, technical discussions, and continuous improvement initiatives.




- Document technical solutions and follow engineering best practices throughout the software development lifecycle.

Required Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline.
- 7–10 years of professional experience in Data Engineering, Data Platform Engineering, or related roles.
- Strong hands-on experience building cloud-native data solutions using AWS services.
- Deep understanding of Snowflake architecture, performance tuning, query optimization, and data modeling best practices.
- Advanced proficiency in Python and SQL for building enterprise-scale data pipelines and transformation frameworks.
- Hands-on experience with Graph Databases (Neo4j, Amazon Neptune, or equivalent).
- Hands-on experience with Vector Databases (Milvus, Amazon OpenSearch, or similar technologies).
- Experience integrating vector databases with LLM-based applications and AI workflows.
- Strong understanding of data warehousing, ETL/ELT design patterns, and scalable pipeline architecture.
- Experience with Git and modern version control workflows.
- Experience using Azure DevOps (AzDO) Boards in Agile development environments.
- Excellent analytical, troubleshooting, and problem-solving skills.
- Solid verbal and written communication skills with the ability to collaborate across cross-functional teams.





Preferred Qualifications

- Experience with workflow orchestration tools such as AWS Step Functions.
- Experience with real-time streaming technologies such as Kafka or Spark Streaming.
- Familiarity with enterprise data governance, security, and compliance frameworks.
- Experience designing AI-ready data platforms supporting semantic search and Retrieval-Augmented Generation (RAG).
- Exposure to Knowledge Graph concepts and graph-based data architectures.
- Experience working with production-scale machine learning or AI data pipelines.

Nice-to-Have Skills

- Knowledge of the NVIDIA ecosystem and GPU-accelerated AI applications.
- Hands-on experience with RAPIDS libraries (cuDF, cuML, cuGraph) or CUDA for high-performance data processing.
- Experience optimizing large-scale data ingestion and transformation workloads using GPU acceleration.

Technical Skills

Required

- AWS (S3, Glue, Lambda, EMR, Redshift)
- Snowflake
- Python
- SQL
- Data Warehousing
- Data Modeling
- ETL / ELT
- Graph Databases (Neo4j, Amazon Neptune)
- Vector Databases (Milvus, Amazon OpenSearch)
- Git
- Azure DevOps
- Agile Methodologies

Preferred
- AWS Step Functions
- Kafka
- Spark Streaming
- LLM Integration
- Retrieval-Augmented Generation (RAG)
- Semantic Search
- Knowledge Graphs
- NVIDIA RAPIDS
- CUDA

Key Competencies

- Cloud Data Engineering
- Snowflake Performance Optimization
- Advanced SQL Development
- Python Development
- Data Pipeline Design
- AI & LLM Data Integration
- Graph & Vector Database Engineering
- Data Quality & Governance
- Performance Optimization
- Problem Solving & Troubleshooting
- Cross-functional Collaboration
- Technical Documentation and Code Reviews

📌 Senior Data Engineer (AWS, Snowflake & AI Data Platforms) (Chennai)
🏢 Applix
📍 Chennai