Applied AI and Data engineer
Chevron · Buenos Aires, Buenos Aires Province, Argentina
- On site
- Full-time
- $120,000 / year
- Buenos Aires, Buenos Aires Province, Argentina
Job highlights
- Engineer automated data pipelines for ML.
- Develop cloud-native solutions on Azure.
- Build LLM and NLP solutions.
- Utilize ML frameworks and libraries.
- Collaborate across global teams.
About the role
Data Engineer - ML Teams at Chevron
Chevron's Business Support Center (BASSC) in Buenos Aires is seeking a Data Engineer for its Machine Learning teams. You will be part of the IT Organization, a global service and technical center with over 1800 employees delivering business services and solutions worldwide.
About the Role
As a Data Engineer, you will leverage software engineering principles to deploy and maintain fully automated data transformation pipelines. You will work with a variety of storage and computation technologies to handle diverse data types and volumes, supporting data architecture design. The goal is to create data products and pipelines that are resilient, modular, flexible, scalable, reusable, and cost-effective.
Required Qualifications
- Minimum 5 years of experience in Object-Oriented Design and Programming with Python.
- Experience implementing machine learning frameworks and libraries.
- Development experience with a JavaScript framework.
- Experience building machine learning pipelines in Microsoft Azure Machine Learning service.
- Experience developing cloud-native solutions using Microsoft Azure Services.
- Experience building multi-agent LLM solutions using Microsoft Azure AI, Databricks, or comparable ecosystems, including tool/function calling, orchestration, guardrails, evaluators, and related capabilities.
- Strong Natural Language Processing (NLP) expertise, including text processing, embedding generation, semantic search, and retrieval optimization.
- Proficiency with Retrieval-Augmented Generation (RAG) patterns, vector indexing, grounding strategies, and metadata-driven retrieval.
Preferred Qualifications
- Experience with Microsoft Copilot Studio (agent creation, orchestration, publishing, custom skills).
- Power Platform integration expertise (custom connectors, end-to-end solution deployment).
- Strong Databricks experience (Unity Catalog, Delta Lake, feature engineering, data pipelines).
- Data engineering and data modeling proficiency, including ETL/ELT workflows and scalable data architectures.
- Familiarity with Responsible AI, security, and privacy best practices in enterprise AI systems.
- Proficiency in applying common design patterns and ability to communicate design ideas effectively.
- Disciplined, methodical, minimalist approach to designing layered software components.
- Hands-on experience deploying machine learning pipelines with Azure Machine Learning SDK.
- Knowledge of enterprise SaaS complexities (security, access control, scalability, high availability, concurrency, diagnostics, deployment, upgrade/migration, internationalization, production support).
- Knowledge of data engineering and transformation tools (DataBricks, Spark, Azure Data Factory).
- Mature software engineering skills (source control, requirement spec, architecture/design review, testing, CI/CD).
- Ability to engage business and technical experts, assess opportunities for ML/analytics, and deliver insights.
- Proven ability to lead projects spanning multiple teams and collaborate with product managers.
- Ability to build collaborative relationships across functional and geographic areas to architect and develop scalable AI solutions.
- Clear, concise, and understandable oral and written communication skills.
Relocation and International Considerations
- Relocation may be considered.
- Expatriate assignments will not be considered.
- Chevron cannot sponsor employment Visas or consider individuals on time-limited Visa status.
Key skills/competency
- Data Engineering
- Machine Learning
- Python
- Microsoft Azure
- LLM Solutions
- NLP
- RAG
- Databricks
- Software Engineering
- Cloud-native Solutions
Skills & topics
- Data Engineer
- Machine Learning
- Python
- Microsoft Azure
- LLM
- NLP
- RAG
- Databricks
- Cloud Engineering
- AI
How to get hired
- Tailor your resume: Highlight Python, Azure, ML, and LLM experience relevant to this Data Engineer role.
- Showcase cloud skills: Emphasize your experience with Microsoft Azure, Azure ML, and Databricks.
- Quantify achievements: Use numbers to demonstrate the impact of your data pipeline and ML solutions.
- Prepare for technical questions: Review OOP, Python, NLP, RAG, and software engineering principles.
- Demonstrate collaboration: Be ready to discuss your experience leading projects and working with diverse teams.
Technical preparation
Master Python for OOP and ML.,Deep dive into Azure ML and services.,Practice LLM, NLP, and RAG concepts.,Build sample data pipelines and models.
Behavioral questions
Describe leading a complex technical project.,How do you ensure data pipeline resilience?,Share an example of collaborating with diverse teams.,How do you assess ML opportunities for business?
Frequently asked questions
- What are the primary responsibilities for a Data Engineer - ML Teams at Chevron?
- The primary responsibilities for a Data Engineer - ML Teams at Chevron involve utilizing software engineering principles to build and maintain automated data transformation pipelines that support machine learning initiatives. This includes developing cloud-native solutions on Microsoft Azure, working with LLM and NLP technologies, and ensuring data products are scalable and cost-effective.
- What technical skills are essential for the Data Engineer role at Chevron?
- Essential technical skills for this Data Engineer role include a minimum of 5 years in Object-Oriented Design and Python development, experience with machine learning frameworks, JavaScript frameworks, Microsoft Azure services (including Azure ML), and building LLM solutions with tools like Azure AI or Databricks. Strong NLP expertise, RAG patterns, and cloud-first solution development are also critical.
- Does Chevron offer relocation assistance for this Data Engineer position?
- Yes, relocation could be considered for this Data Engineer position. However, expatriate assignments are not being considered, and Chevron cannot sponsor employment Visas or consider individuals on time-limited Visa status.
- What is the expected experience level for the Data Engineer - ML Teams at Chevron?
- The role requires a minimum of 5 years of experience in Object-Oriented Design, Python development, and implementing machine learning frameworks. Additional experience with cloud solutions, LLM development, NLP, and specific tools like Azure ML and Databricks is highly valued.
- How does Chevron approach the development of ML solutions?
- Chevron approaches ML solution development by focusing on robust data engineering and software engineering principles. This includes building scalable, resilient, and cost-effective data products and pipelines, integrating multi-agent LLM capabilities, and leveraging technologies like Microsoft Azure AI and Databricks, with a strong emphasis on NLP and RAG patterns.
- What does 'cloud first solutions' mean in the context of this Chevron role?
- Developing 'cloud-first solutions' means designing and building applications and data pipelines with the cloud (in this case, Microsoft Azure) as the primary platform. This involves leveraging cloud-native services, optimizing for scalability, flexibility, and cost-efficiency inherent in cloud environments, and often implies a move away from traditional on-premise infrastructure.