DATA ENGINEER (10+YRS) @ AT&T
We are seeking a highly skilled and experienced Data Engineer to join our team for a long-term contract engagement with AT&T. This role is a 2+ year contract primarily based in the Texas region, specifically looking for candidates who can work in a hybrid onsite capacity in Plano, Dallas, or Richardson. The successful candidate will be responsible for building and optimizing scalable data pipelines and automating complex ETL processes to support large-scale enterprise data initiatives.
Key responsibilities include executing data migrations between Palantir and Snowflake, as well as conducting comparative analyses between these platforms. You will utilize Databricks for automation and pipeline development while collaborating with various stakeholders on data modeling and engineering solutions. The ideal candidate must be eligible for W2 employment and possess a deep technical background in SQL, data transformation, and optimization within cloud environments.
Key responsibilities include executing data migrations between Palantir and Snowflake, as well as conducting comparative analyses between these platforms. You will utilize Databricks for automation and pipeline development while collaborating with various stakeholders on data modeling and engineering solutions. The ideal candidate must be eligible for W2 employment and possess a deep technical background in SQL, data transformation, and optimization within cloud environments.
Key Requirements
Minimum of 10 years of professional experience in data engineering roles.
Expertise in working with Snowflake for data warehousing and management.
Advanced proficiency in SQL, including table building and complex K statements.
Hands-on experience with Palantir for data migration and comparative analysis.
Strong skills in Databricks for automation and data pipeline development.
Proven ability to perform data transformation and performance optimization.
Must be willing and eligible to work on a W2 contract basis.
Experience with Alteryx or similar ETL tools like FME is highly preferred.
Ability to build and maintain scalable data pipelines in a production environment.
Exposure to GIS or ESRI technologies is considered a significant advantage.
Strong analytical skills for troubleshooting complex data sets and migrations.