Lead Data Engineer - AWS
Tiger Analytics Inc. Open · verified Oct 24, 2026 At a glance
Senior Data Engineering role at Tiger Analytics Inc. Remote, United States · full-time · no salary stated · we estimate $142,500–$193,650 across the United States.
Tiger Analytics Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Design AWS data pipelines with Bedrock and SageMaker to build and scale generative AI applications
- Set up vector search for retrieval-augmented generation using OpenSearch Serverless or specialized vector engines
- Create event-driven ETL workflows with Lambda, Glue and Kinesis
- Run data lakehouses on S3, Lake Formation and Redshift, and automate model tuning and deployment with Step Functions and SageMaker Pipelines
What you bring
- You bring eight to twelve years in data engineering, with substantial work on AWS
- You have hands-on experience with Glue, Athena, EMR and Redshift
- You can use LangChain or LlamaIndex with AWS services to work with text, images and PDFs
- You have deployed infrastructure with AWS CDK or Terraform and can build distributed workloads using advanced SQL, Python and PySpark
Who this fits
This senior role suits a data engineer focused on AWS foundations for generative AI, vector search and large-scale data systems. It is listed as remote in Dallas.
From the employer
Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
Tiger Analytics is seeking an experienced Senior Data Engineer to join our team, specifically focused on building scalable Generative AI architectures within the AWS ecosystem. You will architect the data foundations that power LLMs and autonomous agents for our Fortune 500 partners.
Key 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.
Requirements
* Experience: 8-12 years in Data Engineering with a heavy focus on the AWS Cloud stack.
* AWS Expertise: Deep hands-on experience with Glue, Athena, EMR, and Redshift.
* AI/ML Tools: Proficiency in LangChain or LlamaIndex integrated with AWS services to handle unstructured data (text, images, PDFs).
* DevOps & IAC: Experience deploying infrastructure using AWS CDK or Terraform.
* Core Skills: Advanced SQL, Python and PySpark skills tailored for distributed processing on AWS.
Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy,
national origin, ancestry, marital status, protected veteran status, disability
status, or any other basis as protected by federal, state, or local law.
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