Chase Rewards, Senior Associate

JPMorgan Chase & Co.•New York, NY

12h•$85,500 - $155,000

About The Position

As a Senior Associate driving end-to-end data ingestion for the Earnings Engine Platform, you will translate complex business and technical needs into actionable ingestion strategies (including opportunities to incorporate emerging AI capabilities), prioritized backlogs, and clear delivery plans. You will partner closely with engineering, data engineering, analytics, and risk and control stakeholders deliver rewards processing and data publication for card initiatives and modernize platform capabilities while also establishing durable data contracts, quality controls, and SLAs. You will play a key role in improving reliability, transparency, and time-to-onboard so rewards capabilities can be delivered faster with stronger customer outcomes.

Requirements

3+ years of experience (or equivalent expertise) in product management, data platform delivery, or a related domain with measurable delivery outcomes.
Demonstrated ability to own requirements and execution for data integration initiatives, including backlog prioritization and release coordination.
Experience defining data contracts and managing schemas, including versioning and change control to enable safe downstream consumption.
Strong understanding of data quality management, including controls, validation frameworks, reconciliation, and operational issue management.
Strong written and verbal communication skills, able to align technical and non-technical stakeholders through clear, decision-oriented documentation.
Strong organizational skills and ability to juggle multiple projects concurrently
Proven ability to build trust and drive outcomes in a highly matrixed environment with multiple partners and competing priorities.
Demonstrated execution discipline, including the ability to independently drive work from intake through delivery with attention to detail and follow-through.
Strong understanding of data pipeline observability practices, including instrumentation, alerting strategies, and operational readiness reviews.

Nice To Haves

Experience delivering capabilities in regulated environments, partnering effectively with risk, compliance, and privacy stakeholders.
Experience implementing lineage and metadata management practices that improve auditability and accelerate root-cause analysis.
Familiarity with data governance concepts, including data classification, access controls, retention, and consent considerations.
Demonstrated experience driving measurable improvements, such as reduced time-to-onboard, increased SLA attainment, or fewer data incidents
Exposure to rewards, loyalty, payments, or customer engagement data domains and associated operational dependencies.
Experience supporting analytics and downstream consumption needs (e.g., semantic alignment, curated datasets, documentation standards).
Experience creating materials and presenting narratives to a variety of stakeholder types, such as senior leadership, business teams, and technical teams

Responsibilities

Lead end-to-end onboarding for new and existing systems that support rewards data publication use cases, from intake through launch.
Advance and implement frameworks to support data publication and availability for downstream systems and partners (e.g. Audit, Controls).
Define and maintain data contracts, schema standards, and change management processes to reduce downstream breakage and improve interoperability.
Produce clear product and delivery artifacts, including requirements, epics, user stories, acceptance criteria, and release notes that support predictable execution.
Establish and operationalize data quality controls, including validation rules, reconciliation routines, exception handling, and defect triage workflows.
Define, monitor, and continuously improve SLAs/SLOs for data timeliness, completeness, accuracy, and availability, and drive remediation when targets are missed.
Implement lineage, metadata, and documentation practices that improve traceability and audit readiness across the ingestion lifecycle.
Partner with governance, privacy, and risk/compliance stakeholders to ensure appropriate data classification, retention, access controls, and policy adherence.
Maintain clear and thorough documentation on project and platform-level requirements
Create compelling narratives for a variety of stakeholder audiences, related to topics such as project strategy, project progress and blockers, and feasibility
Coordinate cross-functional delivery across product, engineering, analytics, operations, and control partners, proactively managing dependencies and blockers to source integration design using Kafka-based, event-driven ingestion patterns in partnership with engineering and data engineering.