Specialist, Lead Data Engineering

Enterprise Products Partners
July 27, 2021
Houston, TX
Job Type


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. 

Make the most of your talents in a fast-paced environment driven by people who strive for achievement. Enjoy corporate strength, stability, and a rewarding career at a growing industry-leading and diverse operating company with a track record for success. Tap into the professional possibilities of Enterprise Products Company.

We are currently seeking an experienced Data Engineer to join the Big Data and Advanced Analytics department.  As part of the Data Engineering team, the Data Engineer will work closely with Business domain experts and Data Scientists to solve real-world oil and gas midstream problems by unlocking the data asset value and enabling advanced analytics, machine learning, and artificial intelligence.  This individual will provide analytical and technical leadership to the team to advance the data engineering practice within the organization.

Responsibilities include:

  • Work directly with Business domain experts and Data Scientists to understand the analytics objective, recommend and develop solutions, and deliver trusted, cleansed, curated data sets in a timely manner
  • Collect, explore, and prepare data for advanced analytics and machine learning
  • Perform exploratory data analysis and present findings for further analysis
  • Architect and implement high quality analytical applications and data products
  • Automate manual data flows for repeated use and scalability
  • Develop data-intensive applications with API’s and streaming data pipelines
  • Operationalize statistical and machine learning models
  • Assists data analysts and data scientists with data extraction, feature engineering, query optimization, and data processing
  • Implement data quality checks to ensure data accuracy, consistency, and reliability
  • Identify opportunities for data improvements and presents recommendations to management
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