

Jobs via Dice
Data Engineer @ Bentonville, AR (Hybrid Onsite) - W2 Only
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer in Bentonville, AR (Hybrid Onsite) for a 12-month contract. Requires a Bachelor's in Computer Science or related field, 3+ years of data engineering experience, proficiency in Apache Airflow, Apache Spark, and Google Cloud Platform.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 20, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Bentonville, AR
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🧠 - Skills detailed
#Apache Airflow #"ETL (Extract #Transform #Load)" #SQL Queries #Spark (Apache Spark) #BigQuery #Forecasting #Kafka (Apache Kafka) #Computer Science #ML (Machine Learning) #AI (Artificial Intelligence) #Data Engineering #Cloud #SQL (Structured Query Language) #Airflow #Documentation #GCP (Google Cloud Platform) #Monitoring #Scala #Storage #Datasets #Data Quality #Data Access #Dataflow #Apache Spark #Data Processing #Data Pipeline
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, HYR Global Source Inc, is seeking the following. Apply via Dice today!
Role: Data Engineer
Location: Bentonville, AR (4 days onsite/week)
Duration: 12 Months Contract to Hire
W2 Only...
Education Requirement - Bachelor's Degree in: Computer Science, Information Technology, Or related field
Required Qualifications
3+ years (Intermediate) or 5+ years (Specialist) of data engineering experience
Hands-on experience with Apache Airflow for pipeline orchestration
Proficiency in Apache Spark for large-scale data processing
Strong SQL skills including complex query optimization and BigQuery-specific capabilities
Experience with Google Cloud Platform data services: BigQuery, Cloud Storage, Pub/Sub, Dataflow
Solid understanding of ETL/ELT patterns and data warehousing principles
Key Responsibilities
Design and build scalable ETL/ELT pipelines using Apache Airflow, Apache Spark, and Google Cloud Platform Dataflow
Develop and maintain BigQuery data models, schemas, and performance-optimized SQL queries
Build and maintain data pipelines feeding AI/ML feature stores and forecasting models
Collaborate with AI Developers to ensure high-quality, low-latency data access for model training
Manage and optimize Cloud Composer DAGs and pipeline orchestration
Implement data quality monitoring, alerting, and lineage tracking
Participate in data platform architecture decisions and documentation
Preferred Qualifications
Google Cloud Platform Professional Data Engineer certification
Experience supporting ML/AI data infrastructure (feature engineering, training datasets)
Familiarity with real-time streaming (Kafka, Dataflow/Flink)
Retail or large-scale consumer data experience
Thanks & Regards,
Namrata Ahuja | Lead Talent Acquisition - US Staffing
T |
LI-NA1
Dice is the leading career destination for tech experts at every stage of their careers. Our client, HYR Global Source Inc, is seeking the following. Apply via Dice today!
Role: Data Engineer
Location: Bentonville, AR (4 days onsite/week)
Duration: 12 Months Contract to Hire
W2 Only...
Education Requirement - Bachelor's Degree in: Computer Science, Information Technology, Or related field
Required Qualifications
3+ years (Intermediate) or 5+ years (Specialist) of data engineering experience
Hands-on experience with Apache Airflow for pipeline orchestration
Proficiency in Apache Spark for large-scale data processing
Strong SQL skills including complex query optimization and BigQuery-specific capabilities
Experience with Google Cloud Platform data services: BigQuery, Cloud Storage, Pub/Sub, Dataflow
Solid understanding of ETL/ELT patterns and data warehousing principles
Key Responsibilities
Design and build scalable ETL/ELT pipelines using Apache Airflow, Apache Spark, and Google Cloud Platform Dataflow
Develop and maintain BigQuery data models, schemas, and performance-optimized SQL queries
Build and maintain data pipelines feeding AI/ML feature stores and forecasting models
Collaborate with AI Developers to ensure high-quality, low-latency data access for model training
Manage and optimize Cloud Composer DAGs and pipeline orchestration
Implement data quality monitoring, alerting, and lineage tracking
Participate in data platform architecture decisions and documentation
Preferred Qualifications
Google Cloud Platform Professional Data Engineer certification
Experience supporting ML/AI data infrastructure (feature engineering, training datasets)
Familiarity with real-time streaming (Kafka, Dataflow/Flink)
Retail or large-scale consumer data experience
Thanks & Regards,
Namrata Ahuja | Lead Talent Acquisition - US Staffing
T |
LI-NA1





