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Contract Databricks Developer Jobs in Phoenix, AZ

Robustware

AI Quality Engineer Lead

Phoenix, AZ · On-site

$71K - $92K/yr

... Databricks, Kubernetes, containers, APIs, security integrations, and enterprise deployment patterns. Data & API Engineering Strong understanding of API contracts, service orchestration, structured ...

Radix Software, Inc

Data Engineer

Scottsdale, AZ · On-site

$120 - $180/hr

Define and enforce data contracts, metric definitions, and modeling standards that support ... Improve developer experience through better tooling, local development workflows, testing practices ...

Conch Technologies Inc

Data Analyst

Tempe, AZ · On-site

Tempe, AZ (Onsite Tuesday-Thursday) - Local Candidates Only Duration: 6-Month Contract-to-Hire W2 ... Databricks * Azure Machine Learning * Data Lakes & Data Warehousing * Data Governance, Metadata ...

TEKsystems

Azure Platform Engineer

Chandler, AZ · On-site

$70.24/hr

Skills Cloud, Terraform, Azure, Python, databricks Top Skills Details Cloud,Terraform,Azure,Python ... Experience Level Expert Level Job Type & Location This is a Contract position based out of Chandler ...

TEKsystems

Azure Platform Engineer

Chandler, AZ · On-site

$70.24/hr

Skills Cloud, Terraform, Azure, Python, databricks Top Skills Details Cloud,Terraform,Azure,Python ... Experience Level Expert Level Job Type & Location This is a Contract position based out of Chandler ...

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All JobsContract Databricks Developer JobsContract Databricks Developer Jobs in Phoenix, AZ

Contract Databricks Developer information

See Phoenix, AZ salary details

$20

$61

$79

How much do contract databricks developer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for contract databricks developer in Phoenix, AZ is $61.05, according to ZipRecruiter salary data. Most workers in this role earn between $54.90 and $67.55 per hour, depending on experience, location, and employer.

What is a Contract Databricks Developer?

A Contract Databricks Developer is a data engineering professional hired on a temporary or project basis to develop, optimize, and maintain data pipelines and analytics solutions using the Databricks platform. They work with cloud data technologies, Spark, and big data frameworks to support organizations in managing large-scale data processing and analytics tasks. Their responsibilities often include building ETL workflows, collaborating with data scientists, and ensuring data quality and performance in data-driven projects.

What are the key skills and qualifications needed to thrive as a Contract Databricks Developer?

To excel as a Contract Databricks Developer, you need strong expertise in data engineering, big data analytics, and proficiency in programming languages like Python or Scala, typically backed by relevant experience or a degree in computer science. Familiarity with Databricks, Apache Spark, cloud platforms (such as Azure or AWS), and certifications like Databricks Certified Associate Developer are commonly required. Excellent problem-solving, adaptability, and communication skills help you collaborate with clients and teams to deliver tailored data solutions. These competencies are crucial for building scalable data pipelines and efficiently managing large datasets in dynamic project environments.

What are some common challenges faced by Contract Databricks developers when starting a new project?

As a Contract Databricks Developer joining a new project, you may encounter challenges such as quickly understanding the existing data architecture, adapting to the client's specific workflow, and ensuring seamless integration with their cloud infrastructure (often Azure or AWS). You’ll also need to align with established data governance and security protocols while collaborating with data engineers, analysts, and business stakeholders. Effective communication and proactive documentation are key to overcoming these hurdles and delivering value efficiently within the contract period.

What is the difference between Contract Databricks Developer vs Data Engineer?

AspectContract Databricks DeveloperData Engineer
Primary FocusDeveloping and optimizing data pipelines using Databricks platformDesigning, building, and maintaining scalable data architectures
Skills & CertificationsProficiency in Spark, SQL, Python, Databricks platform, and cloud servicesKnowledge of ETL processes, SQL, Python, cloud platforms, and data modeling
Work EnvironmentProject-based, often remote, with a focus on Databricks environmentsVaries from in-house teams to consulting, working on large-scale data systems

While both roles require expertise in data processing and cloud platforms, a Contract Databricks Developer specializes in building data solutions specifically within the Databricks environment, whereas a Data Engineer has a broader scope in designing and managing overall data infrastructure across various tools and platforms.

What are the most commonly searched types of Databricks Developer jobs in Phoenix, AZ?

The most popular types of Databricks Developer jobs in Phoenix, AZ are:

What are popular job titles related to Contract Databricks Developer jobs in Phoenix, AZ?

For Contract Databricks Developer jobs in Phoenix, AZ, the most frequently searched job titles are:

What job categories do people searching Contract Databricks Developer jobs in Phoenix, AZ look for?

The top searched job categories for Contract Databricks Developer jobs in Phoenix, AZ are:

Contract Databricks Developer jobs near you
Infographic showing various Contract Databricks Developer job openings in Phoenix, AZ as of August 2026, with employment types broken down into 83% Full Time, 6% Part Time, and 11% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $126,994 per year, or $61.1 per hour.

AI Quality Engineer Lead

Robustware

Phoenix, AZ • On-site

$71K - $92K/yr

Other

Posted 4 days ago

Job description

Role: AI Quality Engineer Lead 

Role: Onsite, Phoenix, AZ

This role will own the end-to-end quality strategy for AI Marketplace solutions, including QE agent development, AI validation, workflow orchestration, and platform integration. Define standards for AI testing, observability, security, and performance while enabling rapid adoption of reusable QE agents across projects. Provide technical leadership and mentorship to engineering teams building and deploying agentic solutions.

 

Competency Area

Technical Expectations

Agentic AI Architecture

Understanding of AI agents, multi-agent workflows, MCP (Model Context Protocol), orchestration frameworks, tool calling, memory management, RAG patterns, and agent lifecycle management.

AI/LLM Validation & Assurance

Ability to define and implement testing strategies for AI systems including hallucination detection, response quality evaluation, guardrail testing, prompt validation, grounding verification, and reliability testing.

QE Automation Engineering

Strong hands-on experience with Playwright, Selenium, API automation, test frameworks, CI/CD integration, test data management, and automation architecture.

Agent Development & Customization

Ability to configure, extend, and customize agents for project-specific workflows, enterprise tools, APIs, business rules, and testing use cases.

AI Observability & Monitoring

Knowledge of agent telemetry, trace analysis, execution monitoring, prompt/response tracking, drift detection, performance analytics, and operational dashboards.

Cloud & Platform Engineering

Working knowledge of Azure AI, AWS Bedrock, OpenAI, Databricks, Kubernetes, containers, APIs, security integrations, and enterprise deployment patterns.

Data & API Engineering

Strong understanding of API contracts, service orchestration, structured/unstructured data, vector databases, embeddings, and data validation techniques.

Responsible AI & Governance

Experience validating security, privacy, compliance, explainability, bias detection, human-in-the-loop controls, and enterprise guardrails for AI agents.

Performance & Scalability Testing

Ability to validate agent response latency, concurrency, token consumption, workflow scalability, resiliency, and failover behavior.

Solution Architecture & Consulting

Capability to translate business use cases into agentic solutions, define reusable marketplace assets, establish standards, and mentor engineering teams.

Ideal Skill Profile

Must Have

  • Agentic AI / LLM fundamentals
  • Playwright or modern automation framework
  • API testing and integration
  • AI testing and validation
  • Azure AI/OpenAI ecosystem
  • Strong QE architecture background

Good to Have

  • LangChain / LangGraph
  • AutoGen / CrewAI / Semantic Kernel
  • Vector databases
  • MCP-based architectures
  • Kubernetes & containers
  • Prompt engineering

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