Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Lead Data Engineer - AWS
Dallas, Texas, United States
Live, first seen by us 84 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
Tools in this posting
- Python
- SQL
- AWS
- Redshift
- S3
- SageMaker
- Terraform
- PySpark
Source — Tool mentions in context
* 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
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:
* 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.
* 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.
* 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
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.
* 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).
* 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.
* 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.
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).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 13, 202684 days ago
- Recorded sightings
- 190
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 84
Up longer than most. Similar jobs usually come down between day 6 and day 54.
At Tiger Analytics, jobs usually come down by about day 68.
From 11,033 similar postings that came down, and 25 of Tiger Analytics’s. Coming down is not always a hire.
Tiger Analytics is hiring
64 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Its jobs tend to stay up a long time
- 2% of open jobs were reposted
Your next step
Check the employer’s posting for the current role and application details.
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Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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.
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Dallas, Texas, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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