JPMorgan Chase within the Wealth Management division is looking to enhance, design, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable manner.
Requirements
- Advanced proficiency in SQL (e.g., joins and aggregations)
- Working understanding of NoSQL databases
- Proficiency in programming languages such as Python/Java for data processing tasks
- Proficient in Object-Oriented Programming (OOP) concepts, with a strong ability to design and implement robust, reusable, and maintainable code structures across various programming languages
- Experience with cloud platforms, particularly Amazon Web Services (AWS), including EMR, Glue, Lambda, and ECS, to design, deploy, and manage scalable and efficient cloud-based solutions
- Hands-on experience with frameworks like Apache Spark, leveraging its capabilities for large-scale data processing and analytics to drive efficient and insightful data solutions
- Proficiency in Unix scripting, data structures, data serialization formats such as JSON, AVRO, or similar, and big-data storage formats such as Parquet
Responsibilities
- Designs, develops, and maintains robust data pipelines to automate the extraction, transformation, and loading (ETL) of data from various sources into data warehouses or data lakes.
- Integrates data from multiple sources, ensuring consistency, accuracy, and reliability.
- Updates logical or physical data models based on new use cases.
- Supports the review of controls to ensure sufficient protection of enterprise data.
- Reviews and makes customizations in one or two tools to generate a product at the business's or customer's request.
- Executes data solutions by designing, developing, and troubleshooting various components within technical products, applications, or systems.
Other
- Formal training or certification on data engineering disciplines and 2+ years applied experience
- Contributes to the team's culture by promoting collaboration and innovation.
- Collaborates with product owners to understand data requirements and provide solutions.
- Documents data pipeline processes and workflows for future reference and training.
- Understanding of data security best practices and compliance requirements.
