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Databricks Jobs in Arizona (NOW HIRING)

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ · On-site

... Databricks. • Collaborate with business domain managers to define product requirements and identify AI opportunities. • Oversee data science project lifecycles, from ideation to production ...

QuantumClean

Data Scientist

Phoenix, AZ · On-site

The role leverages enterprise analytics platforms including Databricks and Microsoft Copilot Studio to enable AI-assisted insights and intelligent automation for manufacturing and operations users.

KUBRA

Data Engineer

Tempe, AZ · On-site

$109.70K - $131.70K/yr

Build, troubleshoot, and optimize data pipelines using PySpark , Databricks , SQL , and cloud data services * Design and implement data models optimized for analytics, warehousing, and reporting use ...

onsemi

Sr. Manager AI & Data Science

Scottsdale, AZ · On-site

Experience with tools like Databricks, Azure ML, and Snowflake. * Understanding of ERP platform and experience in enabling AI in business functions like sales, HR, finance, operations, etc.

KUBRA

Data Engineer

Tempe, AZ

$109.70K - $131.70K/yr

Build, troubleshoot, and optimize data pipelines using PySpark , Databricks , SQL , and cloud data services * Design and implement data models optimized for analytics, warehousing, and reporting use ...

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$21.9K

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$47.5K

How much do databricks jobs pay per year?

As of May 31, 2026, the average yearly pay for databricks in Arizona is $35,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,200.00 and $38,700.00 per year, depending on experience, location, and employer.

What is a Databricks job?

A Databricks job is a way to run an automated workload, such as a data pipeline, machine learning model training, or ETL task, on the Databricks platform. Jobs can be scheduled, triggered manually, or run as part of a workflow. They support different task types, including notebooks, Python scripts, JARs, and SQL queries. Databricks jobs also allow for dependency management and orchestration across multiple tasks within a workflow.

What are the key skills and qualifications needed to thrive in the Databricks position, and why are they important?

To thrive in a Databricks role, you need strong programming skills in languages such as Python or Scala, a deep understanding of data engineering or data science principles, and typically a relevant degree in computer science or a related field. Experience with Apache Spark, cloud platforms like Azure or AWS, and Databricks-specific certifications are often highly valued. Exceptional problem-solving, communication, and collaboration skills help professionals excel within multidisciplinary data teams. These capabilities are crucial for successfully designing, developing, and optimizing large-scale data solutions in a fast-evolving analytics environment.

What are the typical daily responsibilities of someone working in a Databricks role?

Professionals in Databricks roles typically spend their days developing and maintaining data pipelines, analyzing large datasets, and collaborating with business stakeholders to translate requirements into scalable solutions. They often use tools such as Apache Spark and cloud platforms to design and optimize workflows, while troubleshooting data quality or performance issues that arise. Regular teamwork with data engineers, analysts, and software developers is common, as is participating in sprint planning or code review sessions. Overall, the role combines hands-on technical work with ongoing collaboration to ensure data-driven insights and infrastructure reliability.

Does Databricks pay more than Google?

As a data platform company, Databricks generally offers competitive salaries that can be comparable to or slightly lower than Google's, depending on the role, location, and experience level. Google is known for high compensation packages, especially for engineering and technical roles, often including bonuses and stock options, while Databricks also provides attractive pay and benefits for data engineers, data scientists, and software engineers. Salary differences depend on specific job functions, seniority, and geographic location.
More about Databricks jobs
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What cities in Arizona are hiring for Databricks jobs? Cities in Arizona with the most Databricks job openings:
Databricks jobs near you

Senior Airflow Engineer / Data Orchestration Specialist

Purple Drive Technologies

Phoenix, AZ • On-site

$105.20K - $143K/yr

Full-time

Posted 7 days ago

Job description

Overview:
Job Title: Airflow Engineer - Data Pipeline Automation
Location: Phoenix, AZ (Onsite | Contract)
Employment Type: Contract
Job Summary
We are seeking a highly skilled Airflow Engineer with expertise in designing, optimizing, and maintaining large-scale data workflows. The ideal candidate will have deep knowledge of Airflow architecture, DAG development, CI/CD pipeline management, and cloud integrations (Azure/AWS). This is an onsite contract role in Phoenix, AZ.
Key Responsibilities
  • Airflow Architecture: Design, configure, and optimize Airflow environments, including schedulers, executors (Celery, Kubernetes), and plugins.
  • DAG Development: Build complex, modular, and reusable DAGs to automate data pipelines and workflows.
  • Performance Optimization: Identify bottlenecks and implement orchestration and scheduling best practices.
  • Cloud Integration: Connect Airflow with Azure Data Factory, Databricks, Azure Storage, AWS, and other cloud-native services.
  • CI/CD Management: Develop and maintain CI/CD pipelines for DAG deployment, testing, and version control using Azure DevOps or similar tools.
  • Monitoring & Alerting: Implement logging, monitoring, and alerting frameworks for Airflow jobs to ensure reliability.
  • Documentation & Mentoring: Maintain technical documentation and conduct knowledge-sharing/mentorship sessions with teams.
  • Troubleshooting: Provide expert-level support for Airflow-related incidents and contribute to root cause analysis.
Required Skills
  • Strong expertise in Apache Airflow (architecture, schedulers, executors, plugins).
  • Proficiency in Python (must) and Java (nice to have) for DAG and pipeline development.
  • Hands-on experience with cloud platforms (Azure, AWS) - Data Factory, Databricks, Synapse, Functions, Storage.
  • Familiarity with CI/CD tools (Azure DevOps, Jenkins, GitLab CI/CD).
  • Experience with Docker and Kubernetes for containerized Airflow deployments.
  • Strong troubleshooting, debugging, and performance optimization skills.
  • Excellent communication and collaboration skills.

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