Analyst, Lead Data Engineering Job Listing at Enterprise Products in Houston, TX (Job ID 000GF9)

Description

Tap into the professional possibilities of the largest publicly traded energy partnership that features one of the most diversified cash flow streams in the midstream segment of the energy industry. With dynamic career opportunities and a creative and supportive environment, our unique midstream energy organization offers the chance to share and be recognized for your ideas.  Join our team and increase your opportunities for success.

We are currently seeking an experienced Data Engineer to join the Big Dat and Advanced Analytics department. The Data Engineer will work closely with business domain experts to create an Enterprise Data Lakehouse to support data analytic use cases for the midstream oil and gas operations, engineering, and measurements business units.  Responsibilities include, but are not limited to:

• Design and implement reliable data pipelines to integrate disparate data sources into a single Data Lakehouse.
• Design and implement data quality pipelines to ensure data correctness and building trusted datasets.
• Design and implement a Data Lakehouse solution which accurately reflects business operations.
• Assist with data platform performance tuning and physical data model support including partitioning and compaction.
• Provide guidance in data visualizations and reporting efforts to ensure solutions are aligned to business objectives.
• Automate and optimize the data lifecycle, find insights from raw data, and applying DevOps principle to data pipelines.
• Work with business leaders to deliver custom software solutions meeting data needs.
• Build and support a data platform for data engineering teams to build, deploy and manage applications.

The successful candidate will meet the following qualifications:

• 5 years of experience as a Data Engineer designing and maintaining data pipeline architectures.
• 5 years of in-depth programming experience in Python and SQL.
• 5 years in software development lifecycle experience with software engineering, development, testing, version control, refactoring, and deployment.
• Experience with common Python Data Engineering packages including pandas, Numpy, Pyarrow, Pytest, Scikit-Learn, and Boto3.
• Experience in implementing a Data Lakehouse using Apache Iceberg or Delta Lake.
• Experience with data platform architecture responsible for high-level design, strategy and implementation of data infrastructure, including data modelling, designing scalable architectures and ensuring data governance, security and compliance.
• Knowledgeable of modern data platform technologies including Apache Airflow, Kubernetes, and S3 Object Storage.
• Experience with AWS, Snowflake, dbt and Airbyte is preferred.
• Experience with infrastructure as code, building consistent and repeatable cloud infrastructure.