Join our innovative team and shape the future of software development.

As a Principal Data Engineer at JPMorgan Chase, you provide expertise and data engineering excellence as an integral part of an agile team to enhance, build and deliver data collection, storage, access, and analytic solutions in a secure, stable, and scalable way. You leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various data pipelines and data architectures to support one or more of the firm’s portfolios.

Job Responsibilities

Architects hybrid on-prem and public cloud data platform solutionsDesigns and builds end-to-end data pipelines for ingestion, transformation, and distribution, supporting both batch and streaming workloadsDevelops and owns data products that are reusable, well-documented, and optimized for analytics, BI, and AI/ML consumers. Implements and manages modern data lake and lakehouse architectures, including Apache Iceberg table formatsImplements interoperability across data platforms and tools, including Databricks, Snowflake, Amazon Redshift, AWS Glue, and Lake FormationEstablishes and maintains end-to-end data lineage to support observability, impact analysis, and regulatory requirementsDefines and enforces data quality standards, implementing automated validation and monitoring using frameworks such as Great ExpectationsPartners with governance, risk, and compliance teams to ensure adherence to firmwide data governance, retention, and regulatory policiesDesigns and implements fine-grained data access controls and entitlements, leveraging tools such as ImmutaOptimizes data platforms for performance, scalability, cost efficiency, and reliability. Collaborates closely with product managers, analytics teams, and platform engineers to align data solutions with business needsProvides technical leadership through architecture reviews, code reviews, and design guidance across teamsActs on previously identified opportunities to converge physical, IT, and data security architecture to manage access​. Assists in analyzing critical trends and insights from visualizations and evaluates and selects data visualization tools across firm​

Required qualifications, capabilities, and skills

Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertiseHands-on experience building and operating batch and streaming data pipelines at scaleExperience with Apache Iceberg and modern table formats in lakehouse environmentStrong proficiency with Databricks, Snowflake, Amazon Redshift, and AWS data services such as Glue and Lake FormationExperience implementing data lineage, data quality, and data observability frameworksProven experience with data governance and entitlement platforms (e.g., Immuta)Strong understanding of secure data access patterns in large, regulated environmentsAbility to influence data architecture standards and best practices across multiple teamsFamiliarity w/ sell-side Markets business. Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplinesAbility to present and effectively communicate with Senior Leaders and ExecutivesShows a proficient understanding of existing data management systems and continuous learning to understand new data management systems