Senior Data Engineer: Real-Time Data Pipelines & Spark

UST; Bentonville (AR); On-site; USD 72,000 - 108,000; Full time

Benefits offered by this job

Paid time off

Paid holidays

401(k) with employer matching

Health, dental, and vision insurance

Job summary

UST is seeking a Senior Data Engineer to lead data engineering initiatives in Bentonville, AR. You will design, develop, and maintain ETL/ELT pipelines using Spark and streaming tech to ingest, transform, and deliver data for analytics.

The role requires 8–10 years of experience, strong Python/SQL (Scala/Java a plus), and cloud experience with GCP/Azure. You will build data lakes, data warehouses (BigQuery), and streaming platforms, while ensuring data quality and low latency processing.

Qualifications

• 8–10 years of experience in data engineering or similar roles.
• Strong proficiency in Python, SQL, and ideally Scala/Java.
• Expertise with Apache Spark (Spark SQL, DataFrames, Streaming).
• Experience with Kafka or public/ Pub/Sub messaging systems.
• Cloud experience with GCP and/or Azure data services.
• Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases.
• Familiarity with Airflow, Databricks, Docker, Kubernetes.

Responsibilities

• 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 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 ingest systems to ensure data accuracy and consistency.

Skills

Spark

PySpark

SQL

Scala

Kafka

Flink

GCP

Azure

Snowflake

Redshift

Airflow

Databricks

Docker

Kubernetes

Education

Bachelor's Degree in computer science or equivalent experience

Tools

Docker

Kubernetes

Job description

UST is seeking a Senior Data Engineer to lead data engineering initiatives in Bentonville, AR. You will design, develop, and maintain ETL/ELT pipelines using Spark and streaming tech to ingest, transform, and deliver data for analytics.

The role requires 8–10 years of experience, strong Python/SQL (Scala/Java a plus), and cloud experience with GCP/Azure. You will build data lakes, data warehouses (BigQuery), and streaming platforms, while ensuring data quality and low latency processing.