Analyst, Lead Data Engineering

Enterprise Products Partners L.P; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Enterprise Products Partners L.P. is seeking an experienced Analyst, Lead Data Engineering to architect and implement a cloud-based Data & AI platform supporting AI and analytics across midstream energy units.

You will shape architecture, set standards, and productionize data products and AI models on AWS and on-premises environments. The role emphasizes building batch/streaming pipelines, data cataloging, feature pipelines, and GenAI applications, with emphasis on MLOps, governance, and

Qualifications

• 10+ years of software engineering experience, with at least 2 years in a technical lead role.
• Expert level experience in Python with solid software engineering fundamentals including testing, code reviews, branching policies, version control, design patterns, and API design.
• Experience building data products leveraging Snowflake, DBT, and Airflow.
• Experience delivering classical ML and GenAI systems to production, including MLOps practices such as model registries, pipeline automation, and monitoring.
• Deep AWS experience building data and AI platforms including S3 Tables, Glue, Athena, Lake Formation, SageMaker, Bedrock, Lambda, ECS, RDS, IAM, and VPC.
• Experience in designing and implementing Infrastructure as Code (IaC) using Terraform, AWS CDK, or CloudFormation along with deployment automation with CI/CD pipelines.
• Practical experience with AI-assisted software development workflows using tools such as Claude Code or Cursor to design, implement, test, and refactor code.
• Experience in structuring work for AI coding agents such as writing clear specifications, providing context, breaking tasks down, and reviewing generated output critically.
• Clear communication skills and the ability to work with both technical and non-technical stakeholders.

Responsibilities

• Design and build reliable batch and streaming pipelines, including ingestion of industrial time-series and operational data alongside unstructured document sources
• Establish data modeling, quality, lineage, and cataloging practices for data product development
• Build feature pipelines and curated datasets that serve analytics, ML, and GenAI use cases
• Productionize classical ML models following MLOps practices
• Build GenAI applications such as retrieval-augmented generation over enterprise documents, including chunking, embeddings, vector search, prompt management, and evaluation
• Implement guardrails, observability, and cost controls for LLM-based systems
• Define evaluation approaches that make AI quality measurable and regressions visible
• Build self-service tooling, reusable templates, and CI/CD pipelines so teams can ship data and AI products consistently on AWS and on-premises environments
• Own infrastructure as code, observability, and reliability practices for the platform
• Embed security, governance, and compliance requirements into the platform by design
• Define and implement best practices around AI Assisted Software Development Life Cycle
• Mentor junior engineers in design and code reviews and implementation best practices

Skills

Python

Snowflake

DBT

Airflow

AWS

Terraform

CI/CD

GenAI

LLMs

Software Architecture

Tools

Claude Code

Cursor

Terraform

AWS CDK

Job description

Enterprise Products does not accept unsolicited resumes from recruiting firms. An unsolicited resume submitted by a recruiting firm via email, hardcopy, the Internet or directly to hiring managers will be deemed the sole property of Enterprise Products, and a fee will not be paid in the event the candidate is hired.

Job Description - Analyst, Lead Data Engineering (000H6X)

Job Description

Analyst, Lead Data Engineering - 000H6X

Description

Enterprise Products Partners L.P. is one of the largest publicly traded partnerships and a leading North American provider of midstream energy services to producers and consumers of natural gas, NGLs, crude oil, refined products and petrochemicals. Our services include: natural gas gathering, treating, processing, transportation and storage; NGL transportation, fractionation, storage and import and export terminals; crude oil gathering, transportation, storage and terminals; petrochemical and refined products transportation, storage and terminals; and a marine transportation business that operates primarily on the United States inland and Intracoastal Waterway systems. The partnership’s assets include approximately 50,000 miles of pipelines; 260 million barrels of storage capacity for NGLs, crude oil, refined products and petrochemicals; and 14 billion cubic feet of natural gas storage capacity.

We are currently seeking an experienced Data Engineer to join the AI and Advanced Analytics department. As part of the AI Engineering team, the Lead Data Engineer will architect, design, and implement a cloud based modern enterprise Data & AI platform to support AI and analytic use cases for the midstream oil and gas business units. This individual will shape the architecture, set engineering standards, and write production code across data products, AI models, and platform infrastructure.

Responsibilities include, but are not limited to:

• Design and build reliable batch and streaming pipelines, including ingestion of industrial time-series and operational data alongside unstructured document sources
• Establish data modeling, quality, lineage, and cataloging practices for data product development
• Build feature pipelines and curated datasets that serve analytics, ML, and GenAI use cases
• Productionize classical ML models following MLOps practices
• Build GenAI applications such as retrieval-augmented generation over enterprise documents, including chunking, embeddings, vector search, prompt management, and evaluation
• Implement guardrails, observability, and cost controls for LLM-based systems
• Define evaluation approaches that make AI quality measurable and regressions visible
• Build self-service tooling, reusable templates, and CI/CD pipelines so teams can ship data and AI products consistently on AWS and on-premises environments
• Own infrastructure as code, observability, and reliability practices for the platform
• Embed security, governance, and compliance requirements into the platform by design
• Define and implement best practices around AI Assisted Software Development Life Cycle
• Mentor junior engineers in design and code reviews and implementation best practices

Qualifications

The successful candidate will meet the following qualifications:

• 10+ years of software engineering experience, with at least 2 years in a technical lead role
• Expert level experience in Python with solid software engineering fundamentals including testing, code reviews, branching policies, version control, design patterns, and API design
• Experience building data products leveraging Snowflake, DBT, and Airflow
• Experience delivering classical ML and GenAI systems to production, including MLOps practices such as model registries, pipeline automation, and monitoring
• Deep AWS experience building data and AI platforms including S3 Tables, Glue, Athena, Lake Formation, SageMaker, Bedrock, Lambda, ECS, RDS, IAM, and VPC
• Experience in designing and implementing Infrastructure as Code (IaC) using Terraform, AWS CDK, or CloudFormation along with deployment automation with CI/CD pipelines
• Practical experience with AI-assisted software development workflows using tools such as Claude Code or Cursor to design, implement, test, and refactor code
• Experience in structuring work for AI coding agents such as writing clear specifications, providing context, breaking tasks down, and reviewing generated output critically
• Clear communication skills and the ability to work with both technical and non-technical stakeholders

1100 Louisiana Street, 10th Floor Houston, TX 77002-5227