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Contract Databricks Data Engineer Jobs in Nevada

Lnw

Head of Data

Las Vegas, NV · On-site

... engineering, including cloud data platforms (Snowflake, Databricks, or equivalent), modern data ... by law, regulation or contracts. In order to ensure L&W complies with its regulatory and ...

Light and Wonder, Inc.

Head of Data

Las Vegas, NV · On-site +1

... engineering, including cloud data platforms (Snowflake, Databricks, or equivalent), modern data ... by law, regulation or contracts. In order to ensure L&W complies with its regulatory and ...

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Contract Databricks Data Engineer information

What are some common challenges faced by contract Databricks Data Engineers when integrating data from multiple sources?

As a contract Databricks Data Engineer, you'll often encounter challenges related to integrating diverse data sources, such as on-premises databases, cloud storage, and APIs. These challenges may include handling inconsistent data formats, managing data quality, and ensuring secure data transfers. Additionally, adapting to clients' unique data architectures and optimizing ETL pipelines for performance in a cloud environment are common tasks. Collaboration with data scientists, analysts, and other engineers is critical to ensure data is both accessible and reliable for downstream analytics and machine learning.

What are Contract Databricks Data Engineers?

Contract Databricks Data Engineers are professionals hired on a temporary or project basis to design, build, and maintain data infrastructure using Databricks, a unified analytics platform. They typically work with big data tools, cloud environments, and programming languages like Python or Scala to process and analyze large datasets. Their responsibilities often include developing data pipelines, optimizing data workflows, and collaborating with data scientists and analysts to support business objectives. Because they are contractors, their roles can vary by project and organization, offering flexibility and specialized expertise.

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

To excel as a Contract Databricks Data Engineer, you need strong experience in data engineering, SQL, Spark, and cloud platforms, often supported by a degree in computer science or a related field. Familiarity with Databricks, Apache Spark, Python or Scala, and cloud services like AWS or Azure is typically required, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you work effectively in dynamic, project-based environments. These competencies ensure the efficient design and implementation of scalable data solutions, driving business insights and project success.
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Contract Databricks Data Engineer jobs near you
Lead Artificial Intelligence Engineer

Lead Artificial Intelligence Engineer

Credit One Bank

Las Vegas, NV • On-site

$97K - $128K/yr

Full-time

Posted 27 days ago

Job description

Job Summary:
Credit One Bank is a data-driven financial services company based in Las Vegas. They are seeking a Lead Artificial Intelligence Engineer to develop and produce AI and machine learning solutions that support banking and credit card businesses, focusing on building scalable, explainable, and compliant AI models for various applications.
Responsibilities:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
Qualifications:
Required:
• Develop, train, and optimize ML, deep learning, and Generative AI models.
• Implement data pipelines, feature engineering, and model inference services.
• Deploy and monitor models using enterprise MLOps practices.
• Support model explainability, bias analysis, and regulatory documentation.
• Collaborate with data engineers, risk, and compliance teams.
• 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: 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.
Preferred:
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 3–7 years of experience in AI/ML or data science.
• Experience working with large-scale financial or transactional data is preferred.
Company:
Credit One Bank is a financial services company that offers credit cards, credit score tracking, and fraud protection services. Founded in 1984, the company is headquartered in Las Vegas, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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