at J.P. Morgan
Bulge Bracket Investment BanksPosted 3 days ago
No clicks
**Lead Data Engineer - JPMorgan Chase** As a Lead Data Engineer in Irvine, CA, you'll drive agile teams to build, enhance, and deliver secure, scalable data solutions. Your key responsibilities include designing and operating production-grade data pipelines, evolving data models, translating business requirements, improving data quality, and managing databases. To succeed, you'll bring: - 5+ years in data engineering roles - Proficiency in Python, SQL, NoSQL, and data query paradigms - Experience with data modeling, ETL processes, and interoperability across multiple systems - Hands-on with databases like PostgreSQL, MySQL, MongoDB, and big data analytics engines - Strong analytical, problem-solving, and communication skills Preferred skills include familiarity with GraphQL, a relevant degree, experience with scenario generation, and statistical techniques. Join us to drive innovation, collaboration, and impact across our global organization, with your unique skills shaping a brighter future together.
- Compensation
- Not specified
- City
- Not specified
- Country
- United States
Currency: Not specified
Full Job Description
Location: Irvine, CA, United States
Design, build, and operate production-grade data pipelines that ingest, clean, transform, and aggregate data from disparate sources to deliver trusted data products
Evolve logical and physical data models that create a comprehensive view of user flows, system dependencies, resiliency signals, and risk measures, and develop new models that support prediction and decisioning where appropriate
Translate business, risk, and control requirements into implementable technical designs and a pragmatic delivery plan, partnering with architects, data engineers, analysts, and stakeholders across a matrix organization. You will contribute to the broader data architecture strategy that underpins resiliency analytics and risk modeling, including integration and interoperability across data sources and systems
Implement and continuously improve data quality management, metadata management, and data governance practices to increase reliability, explainability, and auditability, and enable data lineage and traceability across sources, transformations, and curated outputs
Work with modern architectures and patterns (including microservices, event-driven designs, cloud-based data platforms, and Lambda/Kappa patterns) to support scalable and, where needed, near real-time data requirements (per provided job specifications).
Leverage SQL heavily and apply a strong understanding of NoSQL and other database technologies, managing and optimizing databases for performance and efficiency
Follow embed automation and engineering best practices (version control, CI/CD, code review, testing, and documentation) to improve stability and delivery, and use advanced developer tooling to accelerate delivery while operating within firm standards and control requirements
Need to have Modern tooling expectations for this role include: Python programming for data engineering, orchestration, automation, and developer productivity, GitHub Copilot for assisted development, subject to firm approval, policy, and applicable control requirements and Claude Code for assisted development, subject to firm approval, policy, and applicable control requirements
5+ years of relevant experience in data engineering, analytics engineering, or data platform engineering roles, with demonstrated delivery across the data lifecycle from collection through transformation, modeling, and analytics enablement
Strong proficiency in SQL, hands-on programming experience in Python, and experience with data query paradigms including SQL and NoSQL;
Practical experience with data modeling, data integration/ETL processes, and interoperability across multiple business systems, including data migration and mapping complex relational data between systems
Experience with database technologies such as PostgreSQL, MySQL, and MongoDB, including performance optimization and operational management
Familiar with big data and analytics engines/platforms such as Apache Spark and Hadoop, and with open-source analytics/query engines for big data
Experience implementing, or partnering closely on, data quality, metadata, and governance controls that increase reliability and auditability
Understand modern distributed systems patterns including APIs and distributed event streaming, and can operate effectively in cloud-based and event-driven environments
Demonstrate strong analytical and problem-solving skills, attention to detail, and the ability to work independently and collaboratively in a matrix environment, with effective communication skills to build partnerships across business and technology stakeholders
Familiarity with GraphQL is a plus
A degree (or equivalent practical experience) in Computer Science, Information Systems, Data Science, or a related field is preferred (per provided job specifications). Experience with scenario generation and modeling approaches that support resiliency and recovery risk analysis is preferred, particularly where outputs must be explainable and operationally actionable for control stakeholders (per provided job specifications, supplemented with role intent).
Exposure to statistical and analytical techniques and data science methods, including familiarity with data mining techniques, is preferred (per provided job specifications). Experience producing high-quality data architecture artifactssuch as target-state diagrams, data flows and lineage views, and conceptual/logical modelsconsumable by a broad stakeholder group is also preferred (per provided job specifications). Industry accreditation such as TOGAF or cloud/solution architecture certifications is a plus
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase's review of criminal conviction history, including pretrial diversions or program entries.
Promote innovation and collaboration, using your unique talents to create meaningful impact and shape a brighter future together.
Lead Data Engineer
Compensation
Not specified
City: Not specified
Country: United States
**Lead Data Engineer - JPMorgan Chase** As a Lead Data Engineer in Irvine, CA, you'll drive agile teams to build, enhance, and deliver secure, scalable data solutions. Your key responsibilities include designing and operating production-grade data pipelines, evolving data models, translating business requirements, improving data quality, and managing databases. To succeed, you'll bring: - 5+ years in data engineering roles - Proficiency in Python, SQL, NoSQL, and data query paradigms - Experience with data modeling, ETL processes, and interoperability across multiple systems - Hands-on with databases like PostgreSQL, MySQL, MongoDB, and big data analytics engines - Strong analytical, problem-solving, and communication skills Preferred skills include familiarity with GraphQL, a relevant degree, experience with scenario generation, and statistical techniques. Join us to drive innovation, collaboration, and impact across our global organization, with your unique skills shaping a brighter future together.
Full Job Description
Location: Irvine, CA, United States
Design, build, and operate production-grade data pipelines that ingest, clean, transform, and aggregate data from disparate sources to deliver trusted data products
Evolve logical and physical data models that create a comprehensive view of user flows, system dependencies, resiliency signals, and risk measures, and develop new models that support prediction and decisioning where appropriate
Translate business, risk, and control requirements into implementable technical designs and a pragmatic delivery plan, partnering with architects, data engineers, analysts, and stakeholders across a matrix organization. You will contribute to the broader data architecture strategy that underpins resiliency analytics and risk modeling, including integration and interoperability across data sources and systems
Implement and continuously improve data quality management, metadata management, and data governance practices to increase reliability, explainability, and auditability, and enable data lineage and traceability across sources, transformations, and curated outputs
Work with modern architectures and patterns (including microservices, event-driven designs, cloud-based data platforms, and Lambda/Kappa patterns) to support scalable and, where needed, near real-time data requirements (per provided job specifications).
Leverage SQL heavily and apply a strong understanding of NoSQL and other database technologies, managing and optimizing databases for performance and efficiency
Follow embed automation and engineering best practices (version control, CI/CD, code review, testing, and documentation) to improve stability and delivery, and use advanced developer tooling to accelerate delivery while operating within firm standards and control requirements
Need to have Modern tooling expectations for this role include: Python programming for data engineering, orchestration, automation, and developer productivity, GitHub Copilot for assisted development, subject to firm approval, policy, and applicable control requirements and Claude Code for assisted development, subject to firm approval, policy, and applicable control requirements
5+ years of relevant experience in data engineering, analytics engineering, or data platform engineering roles, with demonstrated delivery across the data lifecycle from collection through transformation, modeling, and analytics enablement
Strong proficiency in SQL, hands-on programming experience in Python, and experience with data query paradigms including SQL and NoSQL;
Practical experience with data modeling, data integration/ETL processes, and interoperability across multiple business systems, including data migration and mapping complex relational data between systems
Experience with database technologies such as PostgreSQL, MySQL, and MongoDB, including performance optimization and operational management
Familiar with big data and analytics engines/platforms such as Apache Spark and Hadoop, and with open-source analytics/query engines for big data
Experience implementing, or partnering closely on, data quality, metadata, and governance controls that increase reliability and auditability
Understand modern distributed systems patterns including APIs and distributed event streaming, and can operate effectively in cloud-based and event-driven environments
Demonstrate strong analytical and problem-solving skills, attention to detail, and the ability to work independently and collaboratively in a matrix environment, with effective communication skills to build partnerships across business and technology stakeholders
Familiarity with GraphQL is a plus
A degree (or equivalent practical experience) in Computer Science, Information Systems, Data Science, or a related field is preferred (per provided job specifications). Experience with scenario generation and modeling approaches that support resiliency and recovery risk analysis is preferred, particularly where outputs must be explainable and operationally actionable for control stakeholders (per provided job specifications, supplemented with role intent).
Exposure to statistical and analytical techniques and data science methods, including familiarity with data mining techniques, is preferred (per provided job specifications). Experience producing high-quality data architecture artifactssuch as target-state diagrams, data flows and lineage views, and conceptual/logical modelsconsumable by a broad stakeholder group is also preferred (per provided job specifications). Industry accreditation such as TOGAF or cloud/solution architecture certifications is a plus
This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorgan Chase's review of criminal conviction history, including pretrial diversions or program entries.
Promote innovation and collaboration, using your unique talents to create meaningful impact and shape a brighter future together.
