Data Engineer

Venture Global LNG•Arlington, VA

9d•$150,000 - $155,000•Onsite

About The Position

The Data Engineer develops, designs, and maintains data platform solutions. This position is based at Venture Global LNG’s Arlington, Virginia headquarters, reports to the Director of Business Intelligence, and is structured within IT under the Vice President of Applications. The role builds and maintains cloud data solutions in Azure, creates and documents data architectures, and develops automated, tested data pipelines that turn information from disparate sources into curated datasets for business intelligence and analytics. The Data Engineer works with BI developers, business subject matter experts, source-system owners, and business stakeholders to translate requirements and business changes into effective technical solutions. The role also contributes to future platform architecture for data warehousing, machine learning, streaming analytics, and data visualization, and assists with governance, data quality, training, testing, and documentation.

Requirements

Bachelor’s degree in Computer Science, Data Analytics, Engineering, Mathematics, Business, or a related field of study.
At least 2 years of experience in cloud architecture and data engineering.
Extensive experience implementing data storage solutions, managing and developing data processing, and optimizing Azure data solutions.
Expertise integrating, transforming, and consolidating data from structured and unstructured systems for analytics solutions.
Understanding of parallel processing and data architecture patterns.
Knowledge of data processing languages such as SQL, Python, or Spark.
Experience building secure data processing pipelines using Azure data services.
Ability to self-manage and make independent decisions.
Excellent interpersonal and communication skills, critical thinking, and attention to detail.
Strong work ethic and ability to prioritize effectively, meet deadlines, adapt to changing priorities and business needs, and succeed in a fast-paced environment.
Ability to efficiently summarize and prioritize information.

Nice To Haves

Proficiency with Microsoft Azure Storage Explorer, Azure DevOps, Azure Data Factory, Azure Databricks, Azure Data Lake Gen 2, Unity Catalog, and Git.
Experience coding primarily in Python and Spark.
Experience with agile development and sprint planning.
Strong technical writing skills.

Responsibilities

Build complex data solutions in an Azure Cloud environment.
Maintain Azure components and services.
Develop architecture changes using infrastructure as code.
Create data architecture diagrams for complex data modeling solutions.
Create and maintain data dictionaries to contextualize data from disparate sources.
Enable end-to-end deployment automation using continuous integration and continuous delivery.
Implement pipelines to ingest, standardize, and transform data into business-facing datasets.
Perform unit and integration testing of data pipelines.
Perform data integration at scale with Azure Data Factory.
Use Databricks to transform, curate, and organize data for business intelligence reporting and data analytics.
Work with BI developers and business subject matter experts to translate business requirements into curated datasets for analytics solutions.
Document data pipelines to support maintainability.
Work with source-system owners and business owners to incorporate business changes into data pipelines.
Design data architecture for future platform growth, including data warehousing, machine learning, streaming analytics, and data visualization.
Assist with testing, governance, data quality, training, and documentation efforts.
Participate in business stakeholder requirement workshops to understand, interpret, and translate requirements into technical solutions.