Tempe, AZ

Data Jobs in Tempe, AZ

5 jobs found

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30d ago

AI Engineer

Entertainment Partners Tempe, AZ

Tempe, AZ

30d ago Closed

$140k - $180k/yr Full time Artificial Intelligence Deep Learning Engineer

This position is no longer accepting applications (closed Sep 5, 2026).

Job Description

Entertainment Partners is hiring a Senior Software Engineer to build, train, evaluate, and deploy production AI and agentic systems for its intelligent product suite.

Responsibilities

Design, develop, train, fine-tune, and evaluate machine learning models using PyTorch and related ecosystem libraries (torchvision, torchaudio, torch.nn, torch.optim).
Build and maintain ML training pipelines, experiment tracking workflows, and model evaluation frameworks.
Implement transformer-based models and LLM integrations for production use cases including NLP, information extraction, classification, and generation.
Use parameter-efficient fine-tuning approaches (LoRA, QLoRA, PEFT) to adapt foundation models for EP domains including payroll, residuals, and production management.
Design and implement RAG (Retrieval-Augmented Generation) using vector databases (pgvector, Pinecone, Weaviate) and semantic search pipelines.
Optimize inference for latency and throughput with quantization, batching, and caching for production serving.
Develop and maintain AI evaluation frameworks with automated evals as unit tests to support reliable, safe, production-grade behavior.
Implement LLM-powered agentic workflows using LangChain, LangGraph, and EP’s internal MCP (Model Context Protocol) server architecture.
Build multi-step reasoning pipelines, tool-calling agents, and autonomous task execution systems integrating with EP’s enterprise data and product APIs.
Apply prompt engineering strategies including few-shot templates, chain-of-thought scaffolding, and structured output validation.
Maintain EP AI quality engineering (QE) standards such as failure taxonomy, runtime guardrails, and evidence-driven release gates.
Contribute to EP’s Enterprise Context Engine, a governed zero-data-retention AI context layer exposed via MCP to Tabnine Agent and Claude Code.
Build and maintain MLOps infrastructure for training, experiment tracking (MLflow, Weights & Biases), versioning, and deployment.
Containerize and deploy ML services with Docker and Kubernetes; integrate with CI/CD using GitHub Actions and Azure DevOps.
Monitor model performance in production using drift detection, feedback loops, and automated retraining triggers.
Ensure AI systems meet security, privacy, and compliance needs including data minimization and access control for sensitive payroll data.
Collaborate with data engineering on feature stores, data pipelines, and training data infrastructure.
Partner with the Chief Architect AI & Data and CAIO to define AI architecture patterns and best practices.
Work with product managers, UX designers, and full stack engineers to translate AI capabilities into product features.
Conduct AI/ML code reviews focused on reproducibility, correctness, and production readiness.
Mentor engineers on AI engineering fundamentals, LLM integration patterns, and responsible AI practices.
Stay current with the AI/ML landscape, evaluate new models/frameworks, and assess applicability.
Advance EP’s AI capability maturity by contributing to the PE AI Maturity Scorecard (S1–S3).
Represent EP’s AI engineering practices in Architecture Review Board discussions.

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field.
6–10+ years of professional software engineering experience, including 3+ years focused on ML/AI engineering in production environments.
Expert-level Python proficiency and deep familiarity with the Python ML/AI ecosystem.
Hands-on production experience with PyTorch: nn.Module, custom training loops, autograd, GPU acceleration (CUDA), and model serialization (TorchScript, ONNX).
Experience with Hugging Face libraries: Transformers, Datasets, and PEFT for fine-tuning/adaptation.
Demonstrated ability building RAG pipelines including chunking, embedding models, vector store selection, and retrieval evaluation.
Production experience integrating LLM APIs (OpenAI, Anthropic, open-source via vLLM/Ollama) and building reliable prompt engineering systems.
Experience with LangChain or LangGraph for multi-step agents and tool-calling workflows.
Strong ML fundamentals: supervised/unsupervised learning, loss functions, regularization, evaluation metrics, and statistical validation.
Experience with experiment tracking and reproducible workflows using MLflow, Weights & Biases, or Comet.
Working knowledge of Docker and cloud ML services (AWS SageMaker, Azure ML, or OCI Data Science).
Experience with SQL and NoSQL databases to design pipelines for ML training and inference.

Technologies

Python, PyTorch, torchvision, torchaudio, torch.nn, torch.optim
LoRA, QLoRA, PEFT
RAG, pgvector, Pinecone, Weaviate
quantization, MLflow, Weights & Biases, Docker, Kubernetes
GitHub Actions, Azure DevOps
LangChain, LangGraph, MCP (Model Context Protocol)
Tabnine Agent, Claude Code
TorchScript, ONNX
Hugging Face Transformers, Hugging Face Datasets, CUDA
OpenAI, Anthropic, vLLM, Ollama
Comet, AWS SageMaker, Azure ML, OCI Data Science
SQL, NoSQL, vector databases
Triton Inference Server, TorchServe, Ray Serve
TensorFlow, JAX, OpenCV, Kubeflow, KFServing
Enterprise Context Engine, MLOps, CI/CD

Benefits

Health, Dental, and Vision options
401(k) retirement savings plan and company match
Paid holidays, vacation time, and sick time
Participation in company equity plans
Employee Assistance Program and mental health and wellness programs
Training and development
Annual bonus and merit reviews

Location & Compensation

Tempe, AZ (hybrid)
$140,000 - $180,000 per year

Preferred Qualifications

Experience with additional deep learning frameworks (TensorFlow, JAX) or framework interoperability (ONNX).
Familiarity with computer vision (torchvision, OpenCV) or speech/audio processing (torchaudio) domains.
Experience with model compression techniques: quantization (INT8, FP16, BF16), pruning, distillation.
Experience serving ML models at scale using Triton Inference Server, TorchServe, Ray Serve, or similar.
Contributions to open-source ML projects or published research (papers, patents, or technical blog posts).
Experience with responsible AI frameworks, bias evaluation, and AI governance practices.
Familiarity with MCP (Model Context Protocol) server development for exposing tools to AI agents.
Prior domain experience in payroll, fintech, media, or enterprise SaaS environments.
Experience with Kubernetes-based ML workload orchestration (Kubeflow, KFServing, or similar).
Hybrid work environment: Burbank, CA headquarters with flexible remote schedule.
On-call availability as needed for production AI system incidents and model deployment events.
Access to GPU-accelerated compute environments (cloud-based) for model training workloads.
Ability to sit for extended periods of time at a computer workstation.
Dexterity of hands and fingers to operate a computer keyboard and mouse.
Occasional participation in early-morning or evening sessions to coordinate with distributed teams or international partners.

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1mo ago

Sr Databricks Data Engineer

Deloitte Tempe, AZ

Tempe, AZ

1mo ago Closed

$116k - $229k/yr Full time Azure Azure DevOps Big Data

This position is no longer accepting applications (closed Aug 21, 2026).

Job Description

Deloitte is seeking a Senior Databricks Data Engineer to join the AI and Data practice in Tempe, Arizona on site. This role focuses on designing, building, and optimizing cloud based data engineering solutions to modernize data platforms, enable analytics and AI use cases, and drive data driven decision making across large scale enterprise transformations. The position offers a salary range of USD 116,200 to 229,100 per year and requires a bachelor’s degree in Computer Science, Engineering, or a related field with a minimum of one year of experience.

Responsibilities

Champion Best Practices: Define, document, and promote leading approaches for data architecture, integration, and modeling.
Pipeline Ownership: Design, develop, and maintain robust data pipelines and architectures that support enterprise data needs at scale.
Drive Excellence: Lead initiatives to enhance data quality, operational efficiency, and process scalability.
Team and Technology Lead: Assess, pilot, and integrate new big data and analytics technologies; mentor data engineers and architects to ensure effective project delivery.
Data Governance: Advise on and implement governance, security, and compliance strategies for modern cloud data ecosystems.
Communication: Translate technical concepts and business value for executives, business leads, and technology teams.
DevOps and Automation: Oversee CI/CD practices with tools such as Azure DevOps, AWS Code Pipeline, Jenkins, TFS, or PowerShell to streamline deployments and operations.

Requirements

Ability to work independently and collaboratively within a team.
Strong written and verbal communication skills.
Meticulous attention to detail and quality of work.
Ability to build and maintain professional relationships.
Capacity to lead projects or workstreams.
Ability to manage multiple tasks in a fast paced and dynamic environment.
Strong interpersonal skills and professional demeanor.
Ability to meet deadlines.
Bachelor's degree in Computer Science, Engineering, or a related field.
5+ years of hands on data engineering experience focusing on Databricks on AWS, Azure, or GCP.
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud native databases, storage solutions, and distributed compute platforms.
Experience with data warehousing, 3NF, dimensional modeling, enterprise data lakes, incremental data loads, and metadata driven ingestion and data quality frameworks using PySpark.
1+ year leading complex cross functional data projects and technical teams, including Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and optimization of data pipelines, code, and compute resources.
Willingness to travel up to 50 percent depending on assignment and client needs.
Limited immigration sponsorship may be available.

Qualifications Required

Bachelor's degree in Computer Science, Engineering, or a related field.
5+ years of hands on data engineering experience with a focus on Databricks on AWS, Azure, or GCP.
Experience with Lakehouse architecture, Apache Spark, Delta Lake, cloud native databases, storage solutions, and distributed compute platforms.
Experience with data warehousing, 3NF, dimensional modeling, enterprise data lakes, incremental data loads, and metadata driven ingestion and data quality frameworks using PySpark.
1+ year leading complex cross functional data projects and technical teams, with experience in Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Apache Airflow, Unity Catalog, automated CI/CD pipelines, and performance optimization of data pipelines and compute resources.
Ability to travel 50 percent on average based on project requirements.
Limited immigration sponsorship may be available.

Preferred

Master’s degree in Computer Science, Engineering, or a related field.
Experience across one or more cloud ecosystems (AWS, Azure, GCP) and associated big data services.
Proficiency in tuning and optimizing performance within Databricks and Apache Spark environments.
Experience with Databricks Lakeflow.
Background in artificial intelligence and machine learning solutions.

Technologies

Databricks, Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, Databricks Workflows, Unity Catalog, Databricks Lakeflow
Apache Spark, PySpark
AWS, Azure, GCP
Azure DevOps, AWS Code Pipeline, Jenkins, TFS, PowerShell
Lakehouse architectures, cloud-native databases, and distributed compute platforms
Apache Airflow

The Team

Deloitte's Core AI and Data practice assists organizations in modernizing data platforms, strengthening enterprise data foundations, and scaling analytics and AI capabilities across the business. The team collaborates with clients to architect, engineer, and deploy cloud-based data solutions that improve decision making, drive innovation, and support large-scale transformation. Practitioners work across business and technology functions to solve complex data modernization challenges.

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2mo ago

Databricks Data Engineer

Deloitte Tempe, AZ

Tempe, AZ

2mo ago Closed

$87k - $171k/yr Full time Analytics Artificial Intelligence Azure Databricks

This position is no longer accepting applications (closed Jul 6, 2026).

Job Description

Join Deloitte in Tempe, AZ, onsite, as a Databricks Data Engineer. This role supports analytics and AI initiatives through the design, construction, and continual optimization of cloud-based data pipelines. The position offers a salary range of USD 86,700 to 170,900 per year and the opportunity to work closely with both client teams and Deloitte experts to deliver large-scale data transformation programs. You will gain hands-on experience with Databricks, Apache Spark, Python, and SQL while contributing to the modernization of enterprise data platforms and influencing how data supports decision making and innovation.

Responsibilities

Create and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
Design and manage batch and streaming data workflows that underpin reporting, analytics, and AI use cases.
Apply data architecture, integration, and modeling practices to improve data quality, scalability, and platform performance.
Collaborate with client teams and Deloitte colleagues to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics.
3+ years of experience in data engineering, ETL development, or data platform engineering.
2+ years building data pipelines in Databricks using Apache Spark, Python, and SQL.
Experience implementing data models, data integration patterns, and cloud-based data processing workflows.
Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
Ability to travel approximately 50% on average.
Limited immigration sponsorship may be available.

Technologies

Databricks
Apache Spark
Python
SQL
AWS
Azure
GCP
Delta Lake
Databricks Workflows
Unity Catalog
Git

Preferred

Experience with Delta Lake, Databricks Workflows, and Unity Catalog
Experience using Git-based version control and CI/CD pipelines
Experience supporting batch and streaming data workloads
Experience with data warehousing, lakehouse architecture, and performance optimization
Experience supporting analytics or machine learning data pipelines
Experience working in consulting or client service delivery environments

Accommodation

Information for applicants with a need for accommodation: details available here

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3mo ago

Data Engineer

KUBRA Tempe, AZ

Tempe, AZ

3mo ago Closed

Full time Analytics AWS Business Intelligence

This position is no longer accepting applications (closed Jun 20, 2026).

Job Description

KUBRA is seeking a Data Engineer to join the Product Development - Business Intelligence team in Tempe, AZ, onsite. The role focuses on designing, building, and maintaining scalable data infrastructure and cloud-based pipelines to enable reliable data processing, reporting, and insights.

Responsibilities

Develop, deploy, and maintain scalable cloud data pipelines and ETL workflows to underpin BI and reporting capabilities
Construct and manage data infrastructure across SQL Server, AWS, and cloud-native data platforms
Build, diagnose, and optimize data pipelines using PySpark, Databricks, SQL, and associated cloud services
Create data models tailored for analytics, data warehousing, and reporting scenarios
Collaborate with BI analysts to manage client reporting requirements and support data-driven insights
Automate routine data processes to improve efficiency, consistency, and data quality
Maintain and enhance existing data infrastructure, pipelines, and reporting data flows
Partner with the Product Technical Writer to document data infrastructure, pipelines, models, and processes
Work with Product, BI, Engineering, and Data Analytics teams to ensure dependable reporting and analytics solutions
Share expertise with colleagues and contribute to ongoing improvements of data systems and processes
Stay current with modern data engineering technologies, including Databricks, PySpark, cloud platforms, data modeling, and streaming data tools
Participate in client-facing sessions as required, including design discussions, technical presentations, and training

Requirements

Bachelor's or Master's degree in Computer Science, Statistics, Analytics, Data Engineering, or related field
3–5 years of cloud data engineering experience on a major cloud platform, preferably AWS
Hands-on experience building data pipelines in cloud environments
Proven experience with PySpark
Practical experience with Databricks
Strong SQL proficiency and experience working with SQL Server or similar relational databases
Practical knowledge of data modeling, data warehousing, and BI reporting concepts
Experience designing data models that support analytics, reporting, and business intelligence use cases
Familiarity with BI tools and reporting platforms such as Power BI or Tableau
Experience maintaining, troubleshooting, and optimizing ETL and data pipelines
Experience with streaming data tools such as Kafka or Kinesis is a plus
Experience documenting technical processes, data infrastructure, and pipeline logic
Ability to participate in occasional client-facing design sessions, presentations, or training as needed

Technologies

SQL Server
AWS
PySpark
Databricks
SQL
Power BI
Tableau
Kafka
Kinesis

Benefits

Competitive pay with annual performance-based bonuses
401(k) plan with company matching
Comprehensive medical, dental, and vision coverage with HSA and FSA options
Paid vacation and sick days plus a birthday day off
Two paid volunteer days
Free access to LinkedIn Learning and an education reimbursement program
Free premium Headspace membership
On-site fitness center in the Tempe office
Fully stocked refreshment stations with drinks and snacks
Tickets at Work discounts and memberships

Strengths that shine in this role

Strong problem-solving mindset with emphasis on data quality and reliability
Ability to translate BI and reporting needs into scalable technical data solutions
Effective communication and professionalism when engaging with internal teams and clients
Collaborative approach that builds relationships across technical and non-technical teams
Capacity to influence others, manage conflicts, and drive productive technical discussions
Proactive, self-driven, and capable of working independently in a results-focused environment
Excellent organization and time management when balancing multiple priorities
Comfort with troubleshooting under pressure to support critical reporting needs
Willingness to share knowledge, document work clearly, and contribute to a cohesive team

Skills that matter in this role

Bachelor’s or Master’s degree in Computer Science, Statistics, Analytics, Data Engineering, or related field
3–5 years of cloud data engineering experience on a major cloud platform, preferably AWS
Hands-on experience building data pipelines in cloud environments
Proven experience with PySpark
Practical experience with Databricks
Strong SQL proficiency and experience with SQL Server or similar relational databases
Practical knowledge of data modeling, data warehousing, and BI reporting concepts
Experience designing data models that support analytics, reporting, and BI use cases
Familiarity with BI tools and reporting environments such as Power BI or Tableau
Experience maintaining, troubleshooting, and optimizing ETL/data pipelines
Experience with streaming data tools such as Kafka, Kinesis, or similar technologies is a plus
Experience documenting technical processes, data infrastructure, and pipeline logic
Ability to participate in occasional client-facing design sessions, presentations, or training as needed

Why you will love working here

Competitive compensation with annual performance-based bonuses
401(k) plan with company matching to support your financial future
Robust medical, dental, and vision coverage with HSA and FSA options
Generous paid time off, plus a birthday day off
Two paid volunteer days to contribute to your community
Free access to LinkedIn Learning and an education reimbursement program
Complimentary premium Headspace membership for mental wellness
On-site fitness center at the Tempe location
Refreshment stations with complimentary drinks and snacks
Tickets at Work discounts and memberships for employee perks

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3mo ago

Senior Data Engineer

DriveTime Tempe, AZ

Tempe, AZ

3mo ago Closed

$145k+/yr Full time Senior Analytics Cloud

This position is no longer accepting applications (closed Jun 10, 2026).

Job Description

Senior Data Engineer role in Tempe, AZ (onsite) with DriveTime, offering USD 145,000 per year.

Responsibilities

Lead design and development of robust dbt Core models to convert raw data into trusted, analytics-ready datasets in Snowflake
Architect scalable, high-performance data models to support enterprise reporting, analytics, and AI initiatives
Translate complex business and analytical requirements into efficient ELT solutions through close collaboration with BI, analytics, and business stakeholders
Incorporate data quality, testing, documentation, and lineage best practices to ensure transparent, reliable data across the ecosystem
Use Python to automate, validate data, orchestrate workflows, and monitor ELT pipeline performance
Monitor, tune, and optimize Snowflake queries for performance and cost efficiency
Lead technical design discussions and contribute technically to key data initiatives
Act as a technical lead and mentor, guiding engineers and raising standards across the data transformation lifecycle
Provide thought leadership on modern data transformation patterns, tooling, and architecture to shape enterprise data strategy
Support data governance and metadata enrichment initiatives aligned with enterprise data goals

Requirements

5+ years of experience in data engineering or analytics engineering
Bachelor's degree in Information Technology or related field, or equivalent practical experience
Advanced SQL skills with hands-on experience using dbt Core for data transformation, testing, and documentation
Strong expertise with Snowflake or a similar modern cloud data platform
Proficiency in Python for scripting, automation, and performance tuning
Solid understanding of dimensional modeling, ELT principles, and data warehousing best practices
Experience with Git-based version control and CI/CD workflows such as GitHub, Azure DevOps, or Argo
Proven ability to lead technical initiatives and mentor engineers
Strong collaboration skills with a track record of influencing and driving adoption of modern data engineering best practices

Technologies

dbt Core
Snowflake
SQL
Python
GitHub
Azure DevOps
Argo

What kind of folks are we looking for?

Collaborative leaders who partner across engineering, analytics, and business teams
Clear communicators who translate complex technical concepts for technical and non-technical audiences
Mentors who foster growth and a culture of continuous learning
Strategic thinkers balancing long-term architecture with near-term business needs
Problem solvers who own initiatives, drive innovation, and propagate best practices across the organization

Nice to have

Experience supporting enterprise data governance or metadata management initiatives
Prior involvement in large-scale analytics or AI-driven data platforms

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Data Jobs in Tempe, AZ

AI Engineer

Sr Databricks Data Engineer

Databricks Data Engineer

Data Engineer

Senior Data Engineer

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