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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates advanced proficiency in SQL and Python, with a strong focus on designing and optimizing data pipelines and implementing Generative AI solutions. Capable of translating business needs into scalable data products and AI assets that enhance productivity and operational efficiency.
Highest-signal resume keywords
SQL ProficiencyPython ProficiencyData Pipeline DevelopmentGenerative AI SolutionsCloud Platforms (AWS or GCP)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data TransformationAnalytical Data ModelingMaster Tables CreationPrompt EngineeringLLM IntegrationData EngineeringAnalytics EngineeringData ScienceArtificial IntelligenceEnd-to-End Solution Development
Tools & Technologies
Amazon BedrockGeminiChatGPT/Enterprise
Certifications & Qualifications
Bachelor's Degree in Systems EngineeringBachelor's Degree in Computer ScienceBachelor's Degree in MathematicsBachelor's Degree in Actuarial ScienceBachelor's Degree in Data ScienceBachelor's Degree in Physics
Industry Keywords
Embedded FinanceData ProductsOperational AutomationAI SolutionsData Analytics
Tech Stack
Tools & technologiesAWSCloudGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Design, build, maintain, and optimize scalable production data-transformation pipelines
- Develop and maintain centralized master tables and semantic layers as the business's single source of truth
- Design and implement agentic AI solutions, intelligent assistants, RAG systems, and prompt engineering using technologies such as Amazon Bedrock, Gemini, and ChatGPT/Enterprise
- Optimize heavy data queries and transformations, and improve the efficiency and cost of LLM token consumption
- Translate business and operational needs into analytical and AI assets that automate tasks, improve productivity, and create new Embedded Finance capabilities
- Build robust, scalable, and unified data products for Embedded Finance
- Convert AI and foundation models into practical, integrated solutions that automate operational tasks and improve productivity
- Lead the full data and AI solution lifecycle from pipeline development through production deployment and monitoring
Requirements
What you’ll need- Advanced proficiency in SQL and Python
- Experience designing, developing, and optimizing data pipelines in production environments
- Experience with analytical data modeling and creating master tables/datasets
- Practical experience with Generative AI solutions, including LLM integration, agent development, intelligent assistants, and RAG systems
- Experience with cloud platforms, preferably AWS or GCP
- Prompt engineering and optimization of LLM token consumption/cost
- Completed bachelor's degree/licenciatura in Systems Engineering, Computer Science, Mathematics, Actuarial Science, Data Science, Physics, or related fields
- At least 4 years of cumulative experience in Data Engineering, Analytics Engineering, Data Science, or Artificial Intelligence roles
- Experience developing and implementing end-to-end solutions
- No direct reports; the position has no personnel management responsibility
Benefits
Comp & perks- Hybrid work schedule: 3 days in the office (Monday, Tuesday, and Wednesday) and 2 days working from home
- Reasonable adjustments during the selection process
- Diversity, inclusion, and equal-opportunity commitment