Lead Data Engineer

J.P. Morgan; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorganChase in New York seeks a Lead Data Engineer to build and operate resilient, governable data pipelines and architectures across multiple business functions. You will design end-to-end data products, enable lineage and analytics, and partner across cybersecurity, technology controls, engineers, and stakeholders to deliver production-grade solutions.

The role emphasizes strong SQL, Python, data modeling, and cloud/event-driven approaches, with a focus on scalable, auditable data platforms

Qualifications

• 5+ years of relevant experience in data engineering, analytics engineering, or data platform engineering roles, with delivery across the data lifecycle.
• Strong proficiency in SQL, hands-on Python, and data query paradigms including SQL and NoSQL.
• Experience with data modeling, data integration/ETL, and interoperability across multiple systems.
• Experience with database technologies (PostgreSQL, MySQL, MongoDB) including performance optimization.
• Familiarity with big data engines (Apache Spark, Hadoop) and open-source analytics engines.
• Experience implementing data quality, metadata, and governance controls for reliability and auditability.
• Understand modern distributed systems, APIs, and cloud-based/event-driven environments.
• Strong analytical, problem-solving, and collaboration skills.

Responsibilities

• Design, build, and operate production-grade data pipelines ingesting data from disparate sources to deliver trusted data products
• Evolve data models creating comprehensive views of user flows, resiliency signals, and risk measures
• Translate requirements into technical designs and delivery plans across matrix teams
• Implement and improve data quality, metadata, governance, and data lineage across sources and outputs
• Work with microservices, event-driven designs, cloud platforms, and Lambda/Kappa patterns for scalable data needs
• Leverage SQL heavily and apply NoSQL knowledge to optimize databases for performance
• Follow embed automation and engineering best practices (CI/CD, code review, testing, documentation)
• Adopt modern tooling: Python for data engineering, GitHub Copilot and Claude Code subject to firm approvals

Skills

SQL

Python

NoSQL

Data Modeling

ETL

PostgreSQL

MySQL

MongoDB

Apache Spark

Hadoop

Data Governance

Metadata Management

Cloud

APIs

Event Streaming

Distributed Systems

GitHub Copilot

Education

Bachelor's degree in Computer Science, Information Systems, Data Science, or related field

Equivalent practical experience accepted

Tools

PostgreSQL

MySQL

MongoDB

Apache Spark

Hadoop

Job description

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 JPMorganChase within the Commercial & Investment Bank Operational Resiliency team, 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.

You will design and build resilient, well-governed data products and pipelines that enable end-to-end lineage, high-quality analytics, and scenario generation to model technology resiliency and recovery risk (per provided job specifications). You will partner closely with cybersecurity, technology controls, engineers, and business stakeholders to deliver pragmatic solutions aligned to strategic goals, with a strong bias toward production-grade engineering discipline and measurable operational outcomes (per provided job specifications, supplemented with hiring manager requirements).

Job Responsibilities

• 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

Required Qualifications, Capabilities, and Skills

• 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

Preferred Qualifications, Capabilities, and Skills

• 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 artifacts—such as target-state diagrams, data flows and lineage views, and conceptual/logical models—consumable 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

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Come join the Commercial & Investment Bank Operational Resiliency function to help shape how we make confident, risk informed decisions.