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Databricks Engineer Jobs in Arkansas (NOW HIRING)

Software Engineer III

Bentonville, AR · On-site

$90K - $180K/yr

Software Engineer III Job Location: 811 Excellence Dr, Bentonville, AR 72716 Duties: Coordinates ... Creating automated jobs and Dashboards on Databricks Platform. Setting up centralized governance ...

Data Engineer

Bentonville, AR · On-site

$100K - $120K/yr

Data Engineer Location: Sunnyvale, CA & Bentonville, AR - (On-Site) -     Worknovas is ... Experience with Airflow, Databricks, Docker, Kubernetes is a plus.

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Databricks Unified Data Analytics Platform for advanced data analytics and visualization ...

Data Engineer I

El Dorado, AR · On-site

$101K - $122K/yr

Python, SQL, PySpark) Experience in the use of Infrastructure as Code tools (Databricks Asset ... data engineering pipelines. Writes and executes complete testing plans, protocols, and ...

Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Proficient in Python and SQL - Experience with Docker and ...

Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Proficient in Python and SQL - Experience with Docker and ...

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Databricks Engineer information

See Arkansas salary details

$49.2K

$92.3K

$167.9K

How much do databricks engineer jobs pay per year?

As of Jul 27, 2026, the average yearly pay for databricks engineer in Arkansas is $92,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,600.00 and $109,600.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

What are the key skills and qualifications needed to thrive as a Databricks Engineer, and why are they important?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
Infographic showing various Databricks Engineer job openings in Arkansas as of July 2026, with employment types broken down into 1% As Needed, 94% Full Time, 1% Part Time, and 4% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $92,309 per year, or $44.4 per hour.
AI Cloud Engineer III

$49.50 - $66.25/hr

Other

Posted 8 days ago


Murphy USA rating

4.2

Company rating: 4.2 out of 10

Based on 255 frontline employees who took The Breakroom Quiz

41st of 48 rated convenience stores


Job description

AI Cloud Engineer - Duties and Responsibilities
Develop, deploy, and operate enterprise AI systems, APIs, and model-serving infrastructure that support retail operations at scale, including personalization, forecasting, pricing intelligence, and real-time decisioning across stores, digital channels, and supply chain systems.
Work closely with data scientists, AI engineers, and application teams to integrate, deploy, and support AI capabilities within customer-facing and internal systems, including mobile applications.
Translate AI solutions and business requirements into production-ready implementations, ensuring alignment with organizational standards and roadmaps defined by the Manager of AI Implementation and Strategy.
Build, deploy, and maintain end-to-end AI pipelines, including data ingestion, feature engineering workflows, model training orchestration, deployment, and monitoring in production environments.
Own the operational reliability of AI platforms and services, including uptime, performance, security, and cost optimization.
Provision, configure, and maintain scalable AI and machine learning environments in Microsoft Azure and Databricks to support enterprise AI initiatives.
Support, monitor, and troubleshoot cloud-based services integrated with POS systems, ensuring high availability and responsiveness.
Implement and maintain infrastructure-as-code (IaC), CI/CD pipelines, and automation practices for AI workloads across Azure and Databricks environments.
Monitor system health, model performance, and data pipelines, and proactively resolve issues, optimize workloads, and implement improvements.
Ensure all solutions adhere to enterprise governance, security, and data management policies, including access controls, data privacy, and compliance standards.
Create and maintain technical documentation, runbooks, and operational procedures to support system maintainability, incident response, and knowledge transfer.
Collaborate with architecture and strategy teams by providing feedback from operational experience to improve system design, scalability, and maintainability.
EDUCATION AND EXPERIENCE
Bachelors degree in Computer Science or related field (preferred)
5+ years of experience in Cloud Engineering (preferred)

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