> Markdown version of [/jobs/ext/1814023-data-engineer-iii-python-databricks](https://www.wearedevelopers.com/jobs/ext/1814023-data-engineer-iii-python-databricks). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer III - Python, Databricks - **Company:** JPMorgan Chase & Co. - **Location:** Houston, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Code Generation, Information Engineering, Data Security, Cursor (Graphical User Interface Elements), Information Lifecycle Management, Python (Programming Language), PostgreSQL, MongoDB, NoSQL, Systems Development Life Cycle, Software Deployment, Software Engineering, SQL Databases, Systems Integration, Enterprise Data Management, Data Processing, GitHub Copilot, Prompt Engineering, Data Layers, Containerization, Data Lakes, AWS Glue, Physical Data Models, Data Pipelines, Docker, Databricks - **Published:** July 17, 2026 - **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210759920 ## About the Role * Formal training or certification on software engineering concepts and 3 years applied experience. * Good working knowledge of AWS, Databricks, and Python, Experience across the data lifecycle. * Advanced at SQL, including joins and aggregations, Working understanding of NoSQL databases. * Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns for analysis. * Utilize AWS Cloud Services for developing, deploying, and managing applications at scale. * Proficiency in AI Coding Assistants, Daily use of tools like Cursor, GitHub Copilot, and Claude to accelerate code generation, documentation, and refactoring. * Effective Prompt Engineering, Providing AI models with context, clear goals, relevant source material, and - defined output expectations to generate accurate, usable code. * Critical Evaluation & Validation, Ability to identify hallucination patterns, security vulnerabilities, and logic errors in AI-generated code, ensuring safety before production deployment. * Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity. * Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements., * Familiarity with the Standardized data layer practices (Medallion architecture) * Exposure to Aurora Postgres and MongoDB * Experience developing and supporting AWS GLUE Jobs, Federated Data Lake * Skills in designing efficient data models including normalization, denormalization, and schema design and an understanding around relational and star schemas. * Augmented Development Workflow: Integrating tools into CI/CD pipelines, containerization (e.g., Docker), and leveraging AI to quickly bridge language gaps (e.g., transitioning between Python, JavaScript, or Java). ## Description * Develop workflows and ELT pipelines using Python and Databricks. * Support review of controls to ensure sufficient protection of enterprise data. * Implement data security using entitlements frameworks. * Update logical or physical data models based on new use cases. * Use SQL frequently and understand NoSQL databases * Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements. * Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations. ## Related Videos - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) - [Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization](https://www.wearedevelopers.com/videos/253-data-fabric-in-action-how-to-enhance-a-stock-trading-app-with-ml-and-data-virtualization) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)