What are the responsibilities and job description for the ETL / Python / SQL Data Engineer III position at JPMorgan Chase?
Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.
As a Data Engineer III at JPMorgan Chase within the Infrastructure Platforms Asset Management, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Frequently utilizes SQL and understands NoSQL databases and their niche in the marketplace
- Collaborate closely with cross-functional teams to develop efficient data pipelines to support various data-driven initiatives
- Implement best practices for data engineering, ensuring data quality, reliability, and performance
- Understand the needs of business stakeholders/product owners and develop data visualizations, dashboards and reports
- Contribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflows
- Perform data extraction and implement complex data transformation logic to meet business requirements
- Leverage advanced analytical skills to improve data pipelines and ensure data delivery is consistent across projects
- Monitor and executes data quality checks to proactively identify and address anomalies
- Ensure data availability and accuracy for analytical purposes
- Identify opportunities for process automation within data engineering workflows
- Communicate technical concepts to both technical and non-technical stakeholders
Required qualifications, capabilities, and skills
- Formal training or certification on Data Engineering concepts and 3 years applied experience
- Experience across the data lifecycle
- Advanced at SQL (e.g., joins and aggregations)
- Working understanding of NoSQL databases
- Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis
- Experience customizing changes in a tool to generate product
- 4 years of Data Engineering experience in building and optimizing data pipelines, architectures, and data sets
- Proficiency in object-oriented and object function scripting languages (Python etc.)
- Strong understanding of data visualization principles and experience in creating user-centered designs
- Experience in developing ETL process and workflows for streaming data from heterogeneous data sources
- Willingness and ability to learn and pick up new skillsets
Preferred qualifications, capabilities, and skills
- Experience with data pipeline and workflow management tools (Airflow, etc.)
- Experience working with modern DataLakes: (Snowflake, Databricks etc.)
- Experience in (BI&A and dashboarding tools Qlik and/or Tableau)
- Knowledge of data engineering practices, cloud platforms, automation, and CI/CD pipeline development
