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Databricks Data Engineer Jobs in Nevada (NOW HIRING)

Deloitte

Cyber Data Protection Manager

Las Vegas, NV · Remote

$106K - $143.30K/yr

Bachelor's degree in Cybersecurity, Information Security, Engineering, Computer Science ... M365 security, Databricks, Snowflake) * 3+ years of professional experience developing data ...

Deloitte

Cyber Data Protection Manager

Las Vegas, NV · Remote

$106K - $143.30K/yr

Bachelor's degree in Cybersecurity, Information Security, Engineering, Computer Science ... M365 security, Databricks, Snowflake) * 3+ years of professional experience developing data ...

CreditOne

AVP, Artificial Intelligence

Las Vegas, NV · On-site

Data platforms (Databricks, Snowflake, Synapse) * Responsible AI & Governance * Model ... Programming & Tooling * Python, PyTorch, TensorFlow, JAX * LangChain, semantic search, vector ...

FocusKPI

Marketing Operations Analyst

Henderson, NV

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

FocusKPI

Marketing Operations Analyst

Las Vegas, NV

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

FocusKPI

Marketing Operations Analyst

Sparks, NV

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

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Databricks Data Engineer information

See Nevada salary details

$45.3K

$132.1K

$180.8K

How much do databricks data engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for databricks data engineer in Nevada is $132,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $140,000.00 per year, depending on experience, location, and employer.

What is a Databricks Data Engineer job?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

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

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

What does a typical day look like for a Databricks Data Engineer?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.
More about Databricks Data Engineer jobs
What are the most commonly searched types of Databricks Data Engineer jobs in Nevada? The most popular types of Databricks Data Engineer jobs in Nevada are:
What are popular job titles related to Databricks Data Engineer jobs in Nevada? For Databricks Data Engineer jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Databricks Data Engineer jobs in Nevada look for? The top searched job categories for Databricks Data Engineer jobs in Nevada are:
What cities in Nevada are hiring for Databricks Data Engineer jobs? Cities in Nevada with the most Databricks Data Engineer job openings:
Databricks Data Engineer jobs near you
Infographic showing various Databricks Data Engineer job openings in Nevada as of May 2026, with employment types broken down into 91% Full Time, 4% Part Time, 1% Temporary, and 4% Contract. Highlights an 58% Physical, and 42% Remote job distribution, with an average salary of $132,091 per year, or $63.5 per hour.
AVP, Artificial Intelligence

AVP, Artificial Intelligence

Credit One Bank

Las Vegas, NV

Full-time

Posted 2 days ago

Job description

Description

Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
  • Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
  • Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
  • Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
  • Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
  • Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
  • Oversee model validation, explainability, bias testing, and audit readiness.
  • Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
Position RequirementsCore AI Concepts and Technologies Required:
  • Machine Learning & Modeling
    • Supervised, unsupervised, reinforcement learning
    • Deep learning (CNNs, RNNs, Transformers)
    • Natural Language Processing (NLP) & LLMs
    • Generative AI (diffusion models, fine-tuning, RAG)
    • AI Engineering & MLOps
  • AI Engineering & MLOps
    • Model training, deployment, monitoring, and retraining
    • Feature stores, vector databases, and model registries
    • CI/CD pipelines for ML (MLOps)
    • GPU/accelerator compute architectures
  • Cloud & Infrastructure
    • Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
    • Kubernetes, containerization, microservices
    • Data platforms (Databricks, Snowflake, Synapse)
  • Responsible AI & Governance
    • Model explainability (SHAP, LIME)
    • Fairness, bias detection, model risk controls
    • Privacy-preserving ML techniques (differential privacy, federated learning)
  • Programming & Tooling
    • Python, PyTorch, TensorFlow, JAX
    • LangChain, semantic search, vector embeddings
    • Prompt engineering & LLM orchestration frameworks
  • Excellent communication, problem-solving, and project management skills
  • Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
  • Demonstrate company core values of excellence, ownership, collaboration, and integrity.
Preferred
  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
  • 5-8 + years of experience in AI/ML or data science.
  • Experience working with large-scale financial or transactional data is preferred.
Credit One Bank, N.A. is a data-driven financial services company based in Las Vegas. Founded in 1984, Credit One Bank offers a spectrum of credit card products for people in all stages of financial life. Credit One Bank is an equal opportunity employer committed to diversity and inclusion and does not discriminate against any employee or applicant for employment because of age, race, religion, color, disability, sex, sexual orientation, or national origin. Reasonable accommodations can be made for those who require them, including access to job applications and workplace accommodations. Employment at Credit One Bank is based on mutual consent (also known as at-will). This means that employees and the Bank may terminate the employment relationship at any time, with or without cause and with or without notice. Please contact the recruiter for this position to learn more. Credit One Bank does not accept unsolicited resumes from agencies and is not responsible for related fees.

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