Data Engineer -Software Engineer 4

Job Summary 

• We are looking for a highly motivated and experienced Data Engineer to join our data engineering team. The ideal candidate will have a strong background in building scalable data pipelines using the AWS cloud stack and extensive hands-on experience with Snowflake. Proficiency in Python and SQL, along with graph and vector database technologies, is essential. 
• This role requires strong problem-solving abilities and a proactive mindset to deliver efficient, scalable, and reliable data solutions. 

Key Responsibilities 

• Design, develop, and maintain scalable data pipelines on AWS using services such as S3, Glue, Lambda, Redshift, and EMR. 
• Build and optimize data warehousing solutions using Snowflake, including performance tuning and data modeling. 
• Write efficient and reusable code in Python and SQL for data transformation and processing. 
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements. 
• Integrate vector databases with LLM-based applications and AI workflows. 
• Monitor, troubleshoot, and improve pipeline performance and reliability. 
• Ensure data quality, integrity, and security across all stages of the pipeline. 
• Participate in code reviews, architecture discussions, and continuous improvement initiatives. 

Required Qualifications 

• 7-10 years of experience in data engineering or related roles. 
• Strong hands-on experience with AWS cloud services, including data and AI workloads. 
• Deep understanding of Snowflake architecture, performance tuning, and best practices. 
• Advanced proficiency in Python and SQL for data pipelines, transformations, and services. 
• Hands-on experience with graph databases (e.g., Neo4j, Neptune) and vector databases (e.g., Milvus, Amazon OpenSearch). 
• Experience with version control systems (e.g., Git) and Git workflows. 
• Experience working with Azure DevOps (AzDO) boards for backlog management in Agile environments. 
• Excellent analytical and problem-solving skills. 
• Strong communication and collaboration abilities. 
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 

Nice to Have skills 

• Knowledge of the NVIDIA ecosystem and its applications in data and AI. 
• Exposure to RAPIDS libraries (cuDF, cuML, cuGraph) or CUDA-based tooling for GPU ccelerated data processing, enabling faster transformation and optimization during large-scale ingestion workflows. 

Preferred Qualifications 

• Experience with orchestration tools such as AWS Step Functions. 
• Familiarity with data governance and compliance practices. 
• Exposure to real-time data processing frameworks (e.g., Kafka, Spark Streaming).