IT Data Engineer

Location: Amarillo, TX - Pantex Plant

Job Title: IT Applications Data Engineer

Career Level From: Senior Associate

Career Level To: Specialist

Organization: Mission Systems )

Job Specialty: System Development

A career at Pantex can offer you the opportunity to make a personal impact on our nation. We recognize that excellent employees are absolutely critical for mission success. We are seeking a Data Engineer to design, build, and optimize the high-performance data pipelines and data infrastructure necessary to power enterprise-level Artificial Intelligence (AI), machine learning, and advanced analytics capabilities.

Primary duties include building and maintenance of data pipelines, hands‑on development of robust, scalable Extract, Load, Transform (ELT)/Extract, Transform, Load (ETL) processes, integrating diverse operational and analytical data sources, and ensuring the reliability and quality of all data assets used for modeling and reporting.

Additional duties may include performance tuning of centralized data platforms, implementing Data Ops methodologies, and collaborating closely with Data Architects and Data Scientists to translate data requirements into fully operationalized solutions.

• Build, test, and maintain highly scalable data pipelines for both batch and real‑time data consumption using cloud‑native services and distributed processing frameworks.
• Construct and manage data systems within the modern data stack (e.g., Databricks, Snowflake, or equivalent cloud data warehouse/lakehouse solutions) to ensure optimal data accessibility and performance.
• Write production‑grade code (primarily Python or Scala) to cleanse, transform, and load complex, high‑volume data into structured data models defined by the Data Architect.
• Implement and manage data quality checks, data lineage tools, and pipeline monitoring to ensure data integrity and immediate detection of failures across the data platform.
• Optimize and fine‑tune database performance, query efficiency, and cost management across data storage and processing services in a secure cloud environment.
• Support Data Science teams by providing efficient access to data, developing feature engineering workflows, and integrating model‑ready data into the Machine Learning Operations (MLOps) platform.

• Participate in defining and enforcing Data Operations (Data Ops) and Development, Security and Operations (Dev Sec Ops ) practices for data pipeline automation, testing, and secure deployment.
• Maintain comprehensive documentation of data flows, data dictionaries, and operational runbooks for all production data infrastructure.
• Collaborate with application development teams and application programming interface (API) developers to establish secure and efficient data ingestion points from source systems.
• Work with Data Architects on modeling new data sources to ensure new data assets adhere to established enterprise data standards and architectures.

• Bachelor’s degree in engineering/science/information technology discipline:
  Minimum 2 years of relevant experience.
• OR Master’s degree in engineering/science/information technology discipline.
• OR applicants without a bachelor’s degree may be considered based on a combination of at least 10 years of completed education and/or relevant experience.

• Not Applicable

• Minimum 2 years of relevant experience, with at least 1 year specifically focused on building and managing enterprise‑grade data pipelines and ELT/ETL processes.
• Expert proficiency in Structured Query Language (SQL) and Python or Scala for data manipulation, transformation, and automation.
• Demonstrated experience with distributed processing frameworks (e.g., Apache Spark, Databricks, Snowflake) and cloud-based data services (e.g., Azure Data Factory, Amazon Web Services (AWS) Glue).
• Master’s degree (MS) in a relevant technical field with minimum 3 years of relevant experience.
• Relevant certifications from modern data stack providers (e.g., Databricks Certified Data Engineer, Snowflake…