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# Data Engineer

- **Company:** UST Inc
- **Location:** Bentonville, AR, United States
- **Experience:** Experienced
- **Salary:** $72,000.0 - $108,000.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Computer Programming, Databases, Directed Acyclic Graph (Directed Graphs), Data Architecture, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Relational Databases, Apache Hive, Python (Programming Language), NoSQL, Performance Tuning, Cloud Services, SQL Databases, Data Streaming, Data Processing, Google Cloud, Azure Data Factory, Snowflake, Apache Spark, Database Performance, Data Lakes, Pyspark, Kubernetes, Information Technology, Apache Flink, Integration Frameworks, Real Time Data, Apache Kafka, Video Streaming, Terraform, Data Pipelines, Docker, Databricks
- **Published:** October 28, 2026
- **Apply:** https://diversityjobs.com/career/18795671/Data-Engineer-Arkansas-Bentonville

## About the Role

* Bachelor's degree in computer science, or an equivalent degree.

 * Programming: Strong proficiency in Python, SQL, and potentially Scala/Java.

 * Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, Streaming).

 * Streaming: Experience with messaging queues like Apache Kafka, or Pub/Sub.

 * Cloud: Familiarity with GCP, Azure data services.

 * Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases.

 * Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus. Experience Level

 * Total IT Experience - Minimum 8 years * GCP - 4 + years of recent GCP experience

 * BigQuery, Apache Airflow, Spark/Java/ PySpark

Preferred

 * GCP, GCS, Relational Databases Data Modeling, Kafka , Terraform

## Description

UST is looking for a Data Engineer with Spark & Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML. The ideal candidate will have strong expertise in Google Cloud Platform (GCP), Apache Airflow DAGs, Java/Spark development, and SQL-based data engineering to support large-scale analytics and data transformation initiatives., * Design, develop, and maintain ETL/ELT data pipelines for batch and real-time data ingestion, transformation, and loading using Spark (PySpark/Scala) and streaming technologies (Kafka, Flink).

 * Build and optimize scalable data architectures, including data lakes, data warehouses (BigQuery), and streaming platforms.
 * Performance Tuning: Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectiveness
 * Data Quality: Implement data quality checks, monitoring, and ing systems to ensure data accuracy and consistency.
 * Develop reusable data processing frameworks and components
 * Build and optimize data solutions using SQL, Python, Spark, and cloud technologies such as Azure, AWS, or GCP.
 * Develop and manage data integration workflows using tools like Azure Data Factory, Databricks, Airflow, or Informatica.
 * Ensure data quality, integrity, security, and governance through validation, monitoring, and compliance best practices.
 * Collaborate with business stakeholders, data analysts, and data scientists to deliver reliable, analytics-ready datasets.
 * Monitor, troubleshoot, and optimize data pipelines and database performance to support high-volume data processing and reporting requirements.
 * The role is expected to Work closely with business analysts, data scientists, and application teams across the globe with a mix of associates and suppliers

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.