Description

You're passionate about making data easy to publish, trustworthy to consume, and fast to power AI-driven decisions. Join our Data Publishing & Processing (DPP) organization to lead products that simplify and standardize the end‑to‑end publishing experience across ingestion, transformation, quality, orchestration, and governed delivery. You will help deliver a unified, intelligent platform that reduces time‑to‑publish, lowers cost‑to‑serve, and enforces quality checks and lineage.

As a Product Manager in Data Publishing and Processing team , you will define and execute the strategy for a modern data publishing and processing framework that serves thousands of applications and diverse personas (data engineers, data owners, analysts, and AI agents). You will lead the product lifecycle from discovery to launch and continuous improvement, balancing performance, cost, security, and compliance. Partnering closely with engineering, architecture, governance, and lines of business, you will deliver reusable blueprints, zero‑touch onboarding, and observability that make publishing fast, safe, and self‑service across our managed lake and consumption platforms.

Job Responsibilities

• Develop and own the product strategy and vision for a unified data publishing and processing platform that supports both batch and streaming workloads, and integrates with enterprise catalogs, entitlements, and observability.
• Lead discovery and customer research to translate publisher needs into a prioritized roadmap (e.g., onboarding, ingestion, processing frameworks, and platform adapters).
• Define and deliver reusable solutions for common publishing use cases (e.g., sor‑to‑lake, streaming, transform to refined, externalization to consumption platforms).
• Drive platform capabilities for Onboarding & self‑service ; Orchestration ,Processing (PySpark/SQL/streaming frameworks; serverless where appropriate);Data quality & readiness (DQ/PII checks, contract validation, versioning) ;Catalog & entitlement integration (registration, lineage, access; Observability & SLOs (time‑to‑publish, error rates, cost guardrails) policies)
• Own and maintain the product backlog; write clear requirements and acceptance criteria; ensure value delivery via iterative releases and measurement.
• Establish and track success metrics (e.g., time‑to‑publish, publish error rate, adoption/NPS, cost per dataset, streaming adoption) and course‑correct based on data.
• Partner with platform engineering, governance, SRE/L2, and vendor teams to ensure reliability (multi‑region failover where needed), security, compliance, and cost efficiency at scale.
• Champion a contracts‑first, API‑first approach that prepares the platform for autonomous and AI‑assisted publishing workflows.

Required Qualifications, Capabilities, and Skills

• 8+ years of product management or adjacent experience in data platforms/analytics/cloud in highly matrixed environments, with a track record of shipping platform capabilities at scale.
• Advanced knowledge of the product development lifecycle, discovery methods, and data‑informed prioritization; demonstrated ability to lead end‑to‑end (strategy → ideation → requirements → launch → iteration).
• Hands‑on experience with ETL/ELT tooling and patterns (e.g., Informatica, Ab Initio, dbt, Spark/PySpark/Glue, SQL, Databricks) for batch and streaming
• Working knowledge of modern data lake/lakehouse stacks and table formats (e.g., Iceberg/Delta/Hudi), and how they enable consumption via platforms such as Snowflake.
• Familiarity with orchestration platforms (e.g., Airflow/MWAA), CI/CD, and observability practices for data pipelines (quality, lineage, SLAs/SLOs).
• Practical exposure to serverless and cloud‑native data processing on AWS/Azure/GCP (e.g., Glue, EMR, Databricks, EKS, Lambda), and cost/performance optimization in cloud.
• Experience integrating with data catalogs/metadata systems and entitlement services; comfort with contracts‑as‑code, schema/versioning, and readiness checks.
• Strong communication and stakeholder management skills; ability to translate customer needs into platform capabilities and measurable outcomes.
• Analytical skills to instrument, monitor, and improve platform health and business KPIs (time‑to‑publish, error rates, cost efficiency, adoption/NPS).

Preferred Qualifications, Capabilities, and Skills

• Master's degree in Computer Science, Engineering, Information Systems, or Business.
• Experience building large‑scale enterprise data platforms in financial services or similarly regulated environments, including familiarity with privacy, security, and audit requirements.
• Knowledge of data contracts, semantic/technical lineage, and policy enforcement (entitlements, tag/column/row‑level access).
• Familiarity with API‑first product design, adapter frameworks, and capabilities for self‑service data engineering.

About Us

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 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.

About the Team

\n Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.\n
\n
\n
\n
\n
\n The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.\n