[Remote] Data Engineer (Contract)
Note: The job is a remote job and is open to candidates in USA. Palo Alto Networks is a leading cybersecurity company dedicated to protecting the digital way of life. They are seeking a Staff Data Engineer and Scientist (Contract) to join their Customer Analytics team, where the role involves developing data infrastructure and advanced analytical solutions to drive business operations and customer success initiatives.
Responsibilities
- Design and implement scalable data architectures and datasets that support the organization's evolving data needs, providing the technical foundations for our analytics team and business users
- Support and implement large datasets in batch/real-time analytical solutions leveraging data transformation technologies
- Enable robust data-level security features and build scalable solutions to support dynamic cloud environments, including financial considerations
- Perform code reviews with peers and make recommendations on how to improve our end-to-end development processes
- Own the end-to-end lifecycle of machine learning projects. You'll build and productionize sophisticated models for critical business areas such as marketing attribution, customer churn prediction, case escalation and other relevant use-cases to post-sales
- Play a key role in our generative AI initiatives. You will be responsible for characterizing, evaluating, and fine-tuning AI agents—such as conversational systems that allow users to query massive datasets using natural language—to improve their accuracy, efficiency, and reliability
- Act as an internal consultant to our Go-to-Market (GTM), Global Customer Services (GCS) and Product and Finance teams. You'll translate business challenges into data science use-cases, identify opportunities for AI-driven solutions, and present your findings in a clear, actionable manner
- Your responsibilities will cover the entire project workflow, working with the business to understand the problem, charting a path to solve the problem, feature engineering, model selection and training, robust evaluation, deployment, and, in partnership with the data platform team, ongoing monitoring for performance degradation
Skills
- Experience building and maintain data pipeline both for reporting, analysis and feature engineering
- Experience building and optimizing clean, well-structured analytical datasets for business and data science use cases. This includes Implementing and supporting Big Data solutions for both batch (scheduled) and real-time (streaming) analytics
- Prior experience working extensively within dynamic cloud environments, specifically Google Cloud Services (GCS) BigQuery and Vertex AI
- Prior experience developing dashboards in Tableau/Looker or similar data viz platform
- Expert-level programming skills in Python
- A solid command of SQL for complex querying and data manipulation
- Proven ability to work autonomously, navigate ambiguity, and drive projects from concept to completion
- Prior working experience in Customer Analytics space and customer experience use-cases, e.g. Escalation, Risk predictors, Renewals and efficiency of project delivery in Professional Services space
- Direct experience with generative AI, including hands-on work with LLMs and frameworks like LangChain, LlamaIndex, or the Hugging Face ecosystem
- Experience in evaluating and optimizing the performance of AI systems or agents
- Demonstrated expertise in specialized modeling domains such as causal inference, time-series analysis
- An MS or PhD in a quantitative field like Computer Science, AI, Statistics, or equivalent practical experience or equivalent military experience
Benefits
- Medical
- Dental
- Vision
- 401K
Company Overview