Salary
≈ $131k – $243k per year (Estimated)
Location
In office (Houston)
Seniority
Senior · 10+ years exp
Visa
H-1B filings in 12 months: 3,429 · green card filings: 933
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Sep 29, 2026. JPMorganChase scores A on the Alion truth index.
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.
Backed by Balderton Capital, Radical Partners, team@irregular
As a Senior Manager of Software Engineering, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.
Job responsibilities
- Lead and deliver the integrated modernization plan across application delivery, data engineering, migration, integration, testing, parallel run, operational readiness, production cutover, and decommissioning.
- Lead and develop a high-performing data engineering organization, including staffing, coaching, performance management, delivery quality, succession planning, and continuous improvement.
- Provide inclusive people leadership through regular coaching, mentoring, feedback, career development, and recognition that enables team members to grow and perform at their best.
- Define and execute the data engineering strategy for ingestion, transformation, data quality, metadata, lineage, data products, and analytical consumption.
- Oversee data platform delivery across Snowflake, Databricks, AWS data services, Redshift, S3, and related orchestration and streaming technologies.
- Establish engineering standards for scalable pipelines, reusable frameworks, automated testing, observability, incident response, cost management, security, and supportability.
- Partner with data architecture, governance, analytics, risk, business, and domain teams to establish trusted data ownership, access controls, service levels, and regulatory compliance.
- Coordinate scope, milestones, critical-path activities, readiness criteria, and dependencies across APIs, Kafka and Avro contracts, data models, legacy capabilities, downstream consumers, infrastructure, and external partners.
- Manage program governance, including executive reporting, risk and issue resolution, decisions, change management, dependency escalation, and outcome-based measures, while leading parallel-run, migration, cutover, and decommissioning planning.
- Build strong relationships with senior leaders, product owners, delivery leads, vendors, and dependent programs, communicating complex topics clearly and driving accountability across teams.
Required qualifications, capabilities, and skills
- 10+ years of overall professional experience, including 4+ years in a people leadership role.
- Experience managing complex programs with multiple workstreams, delivery teams, and executive stakeholders.
- Demonstrated success delivering enterprise modernization, platform migration, application transformation, or comparable initiatives.
- Strong experience with program governance, integrated planning, dependency management, risk and issue resolution, and executive communications.
- Ability to understand and communicate technical concepts involving cloud platforms, APIs, event-driven architecture, data platforms, and distributed systems.
- Demonstrated experience managing data engineering teams and delivering enterprise data platforms, pipelines, or analytical data products.
- Strong understanding of modern data engineering practices, including batch and streaming ingestion, data modeling, orchestration, data quality, lineage, governance, and platform reliability.
- Strong analytical, organizational, negotiation, and decision-making skills.
- Hands-on familiarity with Snowflake, Databricks, Delta Lake, Spark, AWS data services, Redshift, S3, and enterprise data integration patterns.
- Bachelor's degree or equivalent experience.
Preferred qualifications, capabilities, and skills
- Experience with finance, lending, originations, servicing, or other financial-services domains.
- Familiarity with AWS, microservices, Kafka, Avro, Camunda or workflow orchestration, and modern data architectures.
- Experience leading data platform modernization, cloud migration, lakehouse adoption, or consolidation of legacy analytical platforms.
- Experience leading legacy-platform replacement, parallel operations, data migration, or production cutover programs.
- Experience establishing technology operating models, delivery metrics, and executive-level governance forums.
- Program or delivery certifications such as PMP, PgMP, SAFe, or equivalent experience.
- Master's degree in business, technology, engineering, or a related discipline.
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