Senior Data Engineer (AWS | Snowflake | Python | SQL)

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.
• Strong 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 **RAP…