Senior Manager of Software Engineering for Data Platform

JPMorganChase•Jersey City, NJ

22h

About The Position

When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.

Requirements

Formal training or certification on software engineering concepts and 5+ years applied experience
Experience leading teams of technologists
Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives
Experience with hiring, developing, and recognizing talent
In-depth knowledge of the services industry and their IT systems
Practical cloud native experience
Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines
Hands-on experience designing and operating distributed, event-driven systems using Java, Spring Boot, and Apache Kafka in production at enterprise scale
Strong working knowledge of stream processing frameworks (Apache Flink or equivalent) and analytical data stores (ClickHouse, Druid, or similar) for real-time aggregation and time-series analytics
Demonstrated experience deploying and operating containerized workloads on Kubernetes (EKS) within AWS, including familiarity with infrastructure-as-code, autoscaling, and production incident response
Proven track record of delivering observability, monitoring, or alerting platforms — including threshold management, anomaly detection, or root-cause/impact-analysis capabilities - in mission-critical environments

Nice To Haves

Experience working with semantic layers or metrics stores (dbt MetricFlow, Cube, LookML, or equivalent) and understanding of the value of governed metric definitions across consuming applications
Background in payments, capital markets, or other regulated financial services domains, with appreciation for data residency, hybrid cloud, and regulatory constraints
Familiarity with Databricks Lakehouse architecture, Apache Iceberg, and modern data engineering patterns including medallion architecture and SCD2 modeling
Experience integrating OpenTelemetry traces and metrics into analytical platforms, and building observability solutions on top of telemetry data
Exposure to access control and policy frameworks (Open Policy Agent, Unity Catalog, attribute-based access control) for enforcing entitlements across federated data sources
Front-end leadership experience overseeing teams building data-dense ReactJS applications, with appreciation for D3.js or similar visualization libraries used in operational dashboards
Experience working in a federated platform model where the engineering team enables domain experts and partner teams rather than owning all business logic centrally

Responsibilities

Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
Be accountable for decisions that influence teams' resources, budget, tactical operations, and the execution and implementation of processes and procedures
Ensures successful collaboration across teams and stakeholders
Identifies and mitigates issues to execute a book of work while escalating issues as necessary
Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team
Creates a culture of diversity, opportunity, inclusion, and respect for team members and prioritizes diverse representation
Lead the design and delivery of a high-throughput, low-latency observability platform built on Java Spring Boot, Kafka, Flink, Databricks, ClickHouse, and ReactJS, ensuring sub-second alerting and accurate impact analysis at payments-scale volumes
Partner with the metrics store platform team to consume governed metric definitions, ensuring observability dashboards, thresholds, and alerts use a single source of truth rather than reimplementing business logic
Drive the technical roadmap for threshold management and alerting capabilities, including static, dynamic, and ML-driven thresholds, and establish patterns for alert routing, suppression, and escalation across operations, sales, and technology stakeholders
Establish engineering excellence standards including CI/CD on EKS, observability of the observability platform itself (OpenTelemetry instrumentation, SLOs, error budgets), and production readiness reviews for new features
Collaborate with domain SMEs and product partners to translate incident-response and impact-analysis workflows into platform capabilities, ensuring the application meaningfully reduces mean-time-to-detect and mean-time-to-resolve for client-impacting events