Job Summary:
Tiger Analytics is a fast-growing advanced analytics consulting firm seeking an experienced Senior Data Engineer to join their team. The role focuses on building scalable Generative AI architectures within the AWS ecosystem, specifically architecting data foundations that power LLMs and autonomous agents for Fortune 500 partners.
Responsibilities:
• GenAI Infrastructure: Architect data pipelines using Amazon Bedrock and Amazon SageMaker to build, deploy, and scale Generative AI applications
• Vector Foundations: Implement and optimize vector search capabilities using Amazon OpenSearch Serverless or specialized vector engines for RAG (Retrieval-Augmented Generation)
• Serverless Data Engineering: Build highly scalable, event-driven ETL pipelines using AWS Lambda, AWS Glue, and Amazon Kinesis
• Modern Data Stack: Manage large-scale data lakehouses leveraging Amazon S3, AWS Lake Formation, and Amazon Redshift
• LLM Ops: Integrate AWS Step Functions and SageMaker Pipelines to automate the fine-tuning and deployment of foundation models
Qualifications:
Required:
• 8-12 years in Data Engineering with a heavy focus on the AWS Cloud stack
• Deep hands-on experience with Glue, Athena, EMR, and Redshift
• Proficiency in LangChain or LlamaIndex integrated with AWS services to handle unstructured data (text, images, PDFs)
• Experience deploying infrastructure using AWS CDK or Terraform
• Advanced SQL, Python and PySpark skills tailored for distributed processing on AWS
Company:
Tiger Analytics offers data analytics and predictive modeling solutions for retail, social media, and online advertising sectors. Founded in 2010, the company is headquartered in Santa Clara, USA, with a team of 5001-10000 employees. The company is currently Late Stage.