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Executive Databricks Developer Jobs in New Jersey

JP Morgan Chase

Principal Software Engineer

Jersey City, NJ

$147K - $198K/yr

Ability to present and effectively communicate with senior leaders and executives Experience in ... Experience with modern data platforms such as Databricks or Snowflake * Deep hands-on experience ...

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Data and Infrastructure Lead - Trade and Working Capital - Vice President

JPMorgan Chase & Co.

Jersey City, NJ • On-site

$150 - $200/hr

Other

Re-posted 11 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 494 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description

Join the Trade and Working Capital (T&WC) Business!

As the Data and Infrastructure Lead (VP) within T&WC, you will drive the data foundation for the Trade and Working Capital business, with direct accountability for the data dictionary, datalake migration, and dashboard reporting design across Snowflake, Databricks, and other BI tools. This role partners closely with the technology data team, product teams, and business data owners to deliver governed, high-quality data that enables scalable analytics and AI use cases

Job responsibilities
  • Lead the design, build, and ongoing management of the Trade and Working Capital data dictionary, including standardized definitions, lineage, and ownership
  • Own the execution of the datalake migration plan, coordinating dependencies across engineering, architecture, and business stakeholders to deliver measurable adoption
  • Drive dashboard and reporting design standards across Snowflake, Databricks, and BI tools to ensure consistent, performant, and decision‑grade insights
  • Establish and enforce data governance practices in partnership with data owners, including data quality controls, stewardship workflows, and issue remediation
  • Translate business priorities into a sequenced data uplift roadmap spanning infrastructure modernization, governance, and AI/advanced analytics enablement
  • Serve as the senior interface between Trade and Working Capital leadership and enterprise technology/data teams, managing alignment, trade‑offs, and delivery commitments
  • Define and monitor KPIs for data platform health, data quality, and reporting outcomes, escalating risks and proposing corrective actions
  • Ensure solutions are designed with financial services control expectations in mind, including auditability, access controls, and appropriate data handling practices
Required qualifications, capabilities and skills
  • Demonstrated leadership delivering data platform and analytics capabilities within complex, matrixed financial services organizations
  • Strong working knowledge of Snowflake and Databricks, including data modeling approaches, performance considerations, and operationalization patterns
  • Proven experience leading datalake migrations or major data platform transitions, with disciplined delivery management and stakeholder alignment
  • Deep understanding of data governance concepts, including metadata management, lineage, stewardship, and data quality frameworks
  • Expertise in dashboard/reporting design principles and BI delivery, including requirements definition, semantic consistency, and adoption management
  • Ability to partner effectively across technology, product, and business data owners, translating between technical constraints and business outcomes
  • Strong program management skills, including roadmap development, prioritization, risk management, and executive communication
  • Sound judgment on data controls and operational resilience expectations typical of regulated environments
Preferred qualifications, capabilities, and skills
  • Experience supporting Trade and Working Capital, transaction banking, or adjacent corporate banking products and operating models
  • Prior ownership of enterprise metadata or data dictionary programs at scale
  • Experience enabling AI/ML use cases through curated datasets, feature‑ready data products, and governed access patterns
  • Familiarity with modern data product operating models and domain‑aligned data ownership
  • Background working across multiple geographies and time zones in a global delivery environment
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