Lead Data Engineer - AWS
Tiger Analytics Inc.over 1 year ago
Remote, United States or Dallas, TX, USAStaff+
Responsibilities
- Architect data pipelines with Amazon Bedrock and Amazon SageMaker for scalable generative AI applications.
- Implement and optimize vector search using Amazon OpenSearch Serverless or specialized vector engines for RAG.
- Build event-driven ETL pipelines with AWS Lambda, AWS Glue, and Amazon Kinesis.
- Manage large-scale data lakehouses using Amazon S3, AWS Lake Formation, and Amazon Redshift.
- Automate foundation-model fine-tuning and deployment with AWS Step Functions and SageMaker Pipelines.
Requirements
- 8–12 years of data engineering experience with a strong focus on AWS.
- Deep hands-on experience with AWS Glue, Amazon Athena, Amazon EMR, and Amazon Redshift.
- Proficiency with LangChain or LlamaIndex integrated with AWS services for unstructured data including text, images, and PDFs.
- Experience deploying infrastructure with AWS CDK or Terraform.
- Advanced SQL, Python, and PySpark skills for distributed processing on AWS.
Benefits
- Remote, full-time position.
- Significant career development in a fast-growing and challenging entrepreneurial environment.
- High degree of individual responsibility.
About Tiger Analytics Inc.
Tiger Analytics Inc. provides data and AI consulting services that deliver machine learning, analytics, and cloud data engineering solutions for large enterprises across industries, including life sciences. The company engages on strategy and implementation projects, from modern BI and data platforms to MLOps, helping Fortune 100 clients turn data into business outcomes. Founded in 2011 and headquartered in Santa Clara, it is privately held with operations across North America, Europe, and Asia-Pacific.