ZipRecruiter

Log In

1

Databricks Vp Jobs (NOW HIRING)

previous pagenext page

Showing results 21-40

All JobsTechnology JobsDatabricks Vp Jobs

Databricks Vp information

See salary details

$43.5K

$157.5K

$277.5K

How much do databricks vp jobs pay per year?

As of Sep 2, 2026, the average yearly pay for databricks vp in the United States is $157,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $190,000.00 per year, depending on experience, location, and employer.

What does a Databricks VP do?

A Databricks VP (Vice President) is a senior executive responsible for leading strategic initiatives, managing teams, and driving business growth in their area of expertise, such as sales, engineering, or product development. They collaborate with other leaders to set company goals, oversee critical projects, and ensure alignment with the organization’s overall vision. The VP also plays a key role in building relationships with clients, partners, and stakeholders to expand Databricks’ market presence. Their leadership helps guide the company’s success in the fast-evolving field of data analytics and artificial intelligence.

What are the main leadership challenges faced by a Databricks VP, and how can candidates prepare to address them?

As a VP at Databricks, you’ll be expected to lead cross-functional teams while driving innovation in a rapidly evolving data and AI landscape. Common challenges include balancing strategic vision with day-to-day operational demands, managing large teams across diverse geographic locations, and ensuring strong alignment between engineering, product, and go-to-market initiatives. Candidates can prepare by developing strong communication and change management skills, gaining experience in scaling teams, and staying well-versed in data and cloud technology trends. Building a track record of fostering collaboration across technical and non-technical stakeholders is also highly beneficial.

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

To thrive as a Databricks VP, you need substantial experience in enterprise technology leadership, deep knowledge of data analytics, and a proven track record in driving business growth, often supported by an advanced degree in business or computer science. Familiarity with cloud platforms (like AWS, Azure), Databricks’ unified analytics platform, and proficiency in data engineering tools are crucial, along with understanding industry certifications. Exceptional leadership, strategic vision, stakeholder management, and communication skills are vital soft skills that set top performers apart in this executive role. These skills ensure alignment between technology and business objectives, drive innovation, and maintain competitive advantage in the data analytics industry.

What is the difference between Databricks Vp vs Data Engineer?

AspectDatabricks VpData Engineer
Required CredentialsAdvanced degrees, leadership experience, cloud platform certificationsBachelor's or master's in CS, data management certifications often preferred
Work EnvironmentStrategic, leadership-focused, overseeing teams and projectsTechnical, hands-on data pipeline development and management
Employer & Industry UsageTech companies, cloud service providers, enterprise data teamsData-driven organizations, analytics teams, IT departments

The Databricks Vp typically focuses on strategic leadership, overseeing data initiatives and teams, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

More about Databricks Vp jobs

What cities are hiring for Databricks Vp jobs?

Cities with the most Databricks Vp job openings:

What are the most commonly searched types of Databricks jobs?

The most popular types of Databricks jobs are:

What states have the most Databricks Vp jobs?

States with the most job openings for Databricks Vp jobs include:

What job categories do people searching Databricks Vp jobs look for?

The top searched job categories for Databricks Vp jobs are:

Databricks Vp jobs near you
Infographic showing various Databricks Vp job openings in the United States as of August 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $157,532 per year, or $75.7 per hour.

Vice President II, Artificial Intelligence (VP of AI)

Credit One Bank

Las Vegas, NV • On-site

Full-time

Re-posted 6 days ago

Job description

Position Summary 

The Vice President of Artificial Intelligence (VP of AI) will lead enterprise-wide AI strategy, innovation, and execution. This role oversees the development, deployment, and governance of AI/ML systems across the organization, ensuring measurable business value, responsible AI practices, and alignment with corporate strategic goals. The VP of AI collaborates closely with Technology, Data, Operations, Risk, Compliance, and Business Unit leadership to build scalable AI platforms, optimize business processes, and accelerate digital transformation.

Essential Job Functions
  • Define and lead the enterprise AI strategy, including advanced analytics, machine learning, deep learning, and generative AI capabilities.
  • Build and oversee AI Centers of Excellence (CoE) to drive innovation, reusable solutions, and best practices.
  • Partner with IT, Data Engineering, and Cloud teams to establish a scalable AI/ML platform and MLOps frameworks.
  • Identify high-impact AI opportunities that drive automation, operational efficiency, customer experience improvements, and revenue growth.
  • Establish standards for Responsible AI, model governance, explainability, bias detection/mitigation, and regulatory compliance.
  • Lead the development, deployment, and lifecycle management of AI/ML models across multiple business units.
  • Oversee the creation of reusable AI components, annotation processes, model training pipelines, and evaluation frameworks.
  • Implement enterprise-wide generative AI solutions including LLMs, copilots, prompt engineering frameworks, and knowledge automation tools.
  • Collaborate with cybersecurity leaders to implement secure AI architectures, data protection controls, and model threat-defense mechanisms.
  • Promote cross-functional collaboration through transparency, communication, and evangelism of AI capabilities.
  • Build and manage high-performing AI teams including machine learning engineers, data scientists, AI product managers, and researchers.
  • Support annual planning, budgeting, strategic roadmaps, and executive-level presentations for AI programs.
  • Continuously monitor emerging AI trends, tools, and technologies and recommend adoption as appropriate.
  • Perform other duties as assigned.
Position Requirements
  • Bachelor’s degree in computer science, Engineering, Data Science, or related field. Master’s or PhD preferred.
  • 12–15+ years of progressive experience in AI/ML, software engineering, or data science, with 7+ years in leadership roles.
  • Demonstrated experience architecting, deploying, and scaling machine learning or deep learning systems in production.
  • Deep knowledge of Responsible AI frameworks, risk controls, and regulatory expectations.
  • Strong experience with cloud platforms (Azure preferred), distributed systems, and MLOps.
  • Exceptional communication skills, with ability to translate complex AI concepts for senior executives.
  • Proven ability to lead and inspire diverse technical teams.
  • Ability to drive outcomes, influence strategic decisions, and deliver business value.
  • Demonstrated alignment with company values of excellence, ownership, collaboration, and integrity.
PreferredCore AI Concepts and Technologies RequiredMachine 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
  • 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
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.  
 

Apply