Lead Data Engineer
Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.
As a Lead Data Engineer at JPMorgan Chase within the Corporate Sector Enterprise Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Provides recommendations and insight on data management, governance procedures, and intricacies applicable to the acquisition, maintenance, validation, and utilization of data
- Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
- Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms
- Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
- Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision
- Adds to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts and 5+ years applied experience
- Strong experience with both relational and NoSQL databases
- Experience and proficiency across the data lifecycle
- Expertise in designing and implementing scalable data architectures and pipelines
- Strong proficiency in programming languages such as Python and PySpark
- In-depth knowledge of data warehousing solutions and ETL processes
- Ability to work collaboratively with cross-functional teams, including data scientists, analysts, and business stakeholders
- Experience with data governance and ensuring data quality and integrity
- Excellent communication skills, with the ability to convey complex technical concepts to non-technical audiences
- Experience with version control systems like Git and CI/CD pipelines for data engineering workflows
Preferred qualifications, capabilities, and skills
- Experience with Trino / Presto
- Proficiency in Big Data technologies, with a strong focus on Performance Optimization using best practices
- Solid understanding of the Parquet file format