Leads data engineering within an agile team, designing secure and scalable data platforms, pipelines, architectures, storage, access, analytics, governance, backup, and recovery strategies. Develops advanced data models, evaluates security controls, documents best practices, and drives responsible AI-assisted engineering adoption. Provides technical leadership through architecture decisions, mentoring, cross-team influence, and operational support using Python, Databricks, Spark, AWS, and modern lakehouse patterns.
Embrace this pivotal role as an essential member of a high performing team dedicated to reaching new heights in data engineering. Your contributions will be instrumental in shaping the future of one of the world’s largest and most influential companies.
As a Senior Lead Data Engineer at JPMorganChase within the Employee Data Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way. Leverage your deep technical expertise and problem solving capabilities to drive significant business impact and tackle a diverse array of challenges that span multiple data pipelines, data architectures, and other data consumers.
Job responsibilities
As a Senior Lead Data Engineer at JPMorganChase within the Employee Data Technology, you are an integral part of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics in a secure, stable, and scalable way. Leverage your deep technical expertise and problem solving capabilities to drive significant business impact and tackle a diverse array of challenges that span multiple data pipelines, data architectures, and other data consumers.
Job responsibilities
- Provides recommendations and insight on data management and governance procedures and intricacies applicable to the acquisition, maintenance, validation, and utilization of data
- Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and design analysis and technical documentation, validating outputs and handling data according to sensitivity and security requirements.
- Designs and delivers trusted data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way
- Defines database back-up, recovery, and archiving strategy
- Generates advanced data models for one or more teams using firmwide approaches, linear algebra, statistical and geometrical algorithms
- Approves data analysis tools and processes
- Creates functional and technical documentation supporting best practices
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
- Evaluates and reports on access control processes to determine effectiveness of data asset security
- Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., validation automation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.
Required qualifications, capabilities, and skills
- Formal training or certification on data engineering concepts with architecture and production ownership concepts and 5+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Strong Python coding skills, and deep experience with Databricks and Spark.
- Experience with both relational and NoSQL databases
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted outputs (e.g., model and design summaries or validation recommendations) before use, escalating when uncertain and following data handling requirements.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Strong experience with AWS and modern lakehouse and data platform patterns.
- Proven technical leadership through architecture decisions, mentoring, and cross-team influence.
Preferred qualifications, capabilities, and skills
- AWS certification and/or Databricks certification.
- Experience with streaming architectures, including event-driven ingestion, near-real-time processing, and operational support for monitoring, alerting, and recovery.
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
JPMorganChase San Francisco, California, USA Office
San Francisco, CA, United States
Similar Jobs
Biotech
Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.
Top Skills:
AirflowAWSAws BedrockDagsterDbtEhrLaboratory Information SystemsLangchainLanggraphLlmsLookerPower BIPrefectPythonRagSalesforceSigmaSnowflakeSnowflake CortexSnowparkSQLTableauTerraform
Artificial Intelligence • HR Tech • Information Technology • Software • Business Intelligence
Leads North American enterprise sales for Qualtrics’ Sports, Media, and Entertainment vertical. Responsibilities include managing and coaching 6–8 enterprise account executives, driving ARR and new-logo growth, developing vertical go-to-market strategies, closing complex seven-figure SaaS deals, engaging executive stakeholders, managing pipelines and forecasts, and partnering with Product Management, Marketing, and Solution Engineering.
Top Skills:
Experience Management PlatformGenerative AiSaaS
Artificial Intelligence • HR Tech • Information Technology • Software • Business Intelligence
Drive enterprise sales growth across healthcare provider accounts by managing strategic relationships, acquiring and expanding clients, presenting tailored solutions, negotiating complex agreements, and coordinating cross-functional teams. Maintain accurate Salesforce records, apply MEDDIC/MEDDPICC methodologies, build pipeline, forecast performance, and achieve new and expansion revenue targets.
Top Skills:
MeddicMeddpiccSaaSSalesforce
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
