Role Overview

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 cloud-based data platforms using the AWS ecosystem and Snowflake . This role requires expertise in developing high-performance data pipelines, data warehousing, and modern data architectures, along with strong proficiency in Python and SQL .

The successful candidate will also have experience working with graph and vector databases , enabling AI/LLM-powered applications, and will collaborate closely with data scientists, analysts, and business stakeholders to deliver reliable, scalable, and secure data solutions.

Key Responsibilities

- Design, develop, and maintain scalable, secure, and high-performance data pipelines using AWS services such as S3, Glue, Lambda, Redshift, EMR, and Step Functions .
- Develop and optimize enterprise-scale data warehousing solutions using Snowflake , including data modeling, performance tuning, and cost optimization.
- Build efficient ETL/ELT pipelines using Python and SQL for large-scale data ingestion, transformation, and processing.
- Design and implement data integration solutions across multiple structured and unstructured data sources.
- Develop and maintain graph and vector database solutions to support AI, machine learning, and LLM-based applications.
- Collaborate with data scientists, business analysts, product teams, and stakeholders to understand business requirements and translate them into scalable data solutions.
- Monitor, troubleshoot, and optimize pipeline performance, reliability, and data quality.
- Implement best practices for data governance, security, compliance, and lifecycle management.
- Participate in architecture discussions, technical design reviews, and code reviews to promote engineering excellence.
- Maintain CI/CD pipelines and version-controlled repositories using Git and Agile development practices.




- Utilize Jira or Azure DevOps (AzDO) boards for sprint planning, backlog management, and Agile project tracking.

Required Technical Skills Cloud & Data Engineering

- Amazon Web Services (AWS)
- S3
- Glue
- Lambda
- Redshift
- EMR
- Step Functions

Data Warehousing

- Snowflake
- Data Modeling
- Performance Tuning
- Query Optimization
- Data Architecture

Programming

- Python
- SQL

Databases

- Graph Databases
- Neo4j
- Amazon Neptune
- Vector Databases
- Milvus
- Amazon OpenSearch (Vector Engine)

Data Engineering Concepts

- ETL / ELT Development
- Data Pipeline Design
- Data Transformation
- Data Integration
- Data Quality Management

DevOps & Agile

- Git
- Git Workflows
- Azure DevOps (AzDO)
- Agile/Scrum Methodology

Required Qualifications

- 5–8 years of professional experience in Data Engineering or related roles.
- Robust hands-on experience building scalable data solutions on the AWS Cloud Platform .
- Extensive experience designing and optimizing Snowflake data warehouse solutions.
- Advanced programming expertise in Python and SQL .
- Experience working with graph databases such as Neo4j or Amazon Neptune .
- Experience implementing vector database solutions such as Milvus or Amazon OpenSearch .
- Strong understanding of modern data architecture and distributed data processing concepts.
- Experience with version control systems and collaborative Git workflows.
- Familiarity with Azure DevOps boards for Agile project execution.
- Excellent analytical, troubleshooting, and problem-solving skills.




- Strong 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 .
- Knowledge of data governance, metadata management, and regulatory compliance practices.
- Experience with real-time data processing technologies such as Apache Kafka and Spark Streaming .
- Exposure to containerization and cloud-native deployment practices (Docker, Kubernetes) is a plus.
- Experience designing AI-ready data platforms supporting Machine Learning and Generative AI workloads.

Nice to Have

- Working knowledge of the NVIDIA AI ecosystem and GPU-accelerated computing.
- Experience with RAPIDS libraries including:
- cuDF
- cuML
- cuGraph
- Familiarity with CUDA-based technologies for accelerating large-scale data transformation and ingestion workloads.
- Exposure to LLM frameworks, Retrieval-Augmented Generation (RAG), and AI data pipelines.

Soft Skills

- Strong analytical and critical thinking abilities.
- Excellent communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Proactive mindset with strong ownership and accountability.
- Adaptability to work in a fast-paced, Agile development environment.
- Continuous learning attitude with a passion for emerging cloud and AI technologies.

Education

- Bachelor's or Master's degree in Computer Science , Information Technology , Engineering , or a related technical discipline.

Why Join Us?

- Work on enterprise-scale cloud data platforms and AI-driven solutions.
- Build modern data architectures leveraging AWS, Snowflake, and next-generation database technologies.
- Collaborate with cross-functional teams in a highly innovative and Agile setting.
- Opportunity to work on cutting-edge AI, machine learning, and Generative AI initiatives while driving impactful business outcomes.

📌 Lead Data Engineer (AWS | Snowflake | Python | SQL) (Hyderabad)
🏢 Applix
📍 Hyderabad