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# SeniorData Engineer

- **Company:** UST Inc
- **Location:** Bentonville, AR, United States
- **Experience:** Expert
- **Salary:** $72,000.0 - $108,000.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Airflow, Big Data, BigQuery, Cloud Computing, Computer Programming, Databases, Data Architecture, Extract Transform Load (ETL), Data Warehousing, Apache Hive, Python (Programming Language), NoSQL, Performance Tuning, SQL Databases, Data Streaming, Data Processing, Data Ingestion, Azure Data Factory, Snowflake, Apache Spark, Event Driven Architecture, Data Lakes, Pyspark, Kubernetes, Information Technology, Apache Flink, Real Time Data, Apache Kafka, Video Streaming, Stream Processing, Data Pipelines, Docker, Databricks
- **Published:** August 21, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18019772?backUrl=%2Fcareer%2F18019772%2FSeniordata-Engineer-Arkansas-Bentonville

## About the Role

* 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 and Skills:

 * Minimum 8 years overall

 * GCP - 4 + years of recent GCP experience

 * Qualification:

 * Bachelor's Degree in computer science or equivalent experience

## Description

* As a Senior Data Engineer, you will 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.

 * Design, develop, and maintain scalable ETL/ELT pipelines for batch and real-time data processing.

 * Build data ingestion frameworks to collect data from multiple sources including databases, APIs, files, and streaming systems.

 * Design and implement real-time streaming solutions using Apache Kafka and Apache Flink.

 * Develop event-driven architectures for low-latency data processing and analytics.

 * Monitor and optimize streaming applications for throughput, scalability, and reliability.

 * Manage Kafka topics, partitions, consumer groups, and stream processing pipelines.

 * 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.

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


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