Lead Software Engineer - Parametric

Morgan Stanley•New York, NY

9h•Hybrid

About The Position

Morgan Stanley is a leading global financial services firm. Parametric, part of Morgan Stanley Investment Management, specializes in building custom portfolios for advisors, institutions, and consultants. This role is part of Parametric's Core Operations Platform team, which aims to create a unified technology ecosystem for efficient, scalable, and controlled execution of Client and Market Operations processes. The Performance Reporting team within this platform designs and operates a resilient, scalable AWS platform to deliver performance and reporting data, aggregating and transforming data using event-driven and Serverless AWS technology, and migrating legacy applications to a modern platform. The Lead Software Engineer will provide technical leadership, project management, process development, training, and support for the Core Operations Platform, with a primary focus on the Performance Reporting engine. This role involves driving the modernization of legacy systems onto a scalable, event-driven, AWS cloud-native architecture, partnering with business analysts and operations stakeholders to meet accuracy, latency, and traceability standards for client reporting, regulatory compliance, and investment decision support.

Requirements

8+ years of hands-on Software Engineering experience
Bachelor’s degree in computer science, or related field (advanced degree a plus)
Expert-level Python — including async patterns, performance optimization, and library ecosystem
5+ years of cloud-native development on AWS (Lambda, Step Functions, Batch, S3, Athena, Glue)
Experience supervising and guiding software development teams and fostering an engaging, collaborative environment.
Demonstrated experience architecting highly available, distributed, event-driven systems
Hands-on experience with Apache Kafka or equivalent streaming/messaging platforms
Strong experience working with relational databases, SQL, and NoSQL data stores (e.g., DynamoDB)
Strong data modeling expertise — relational, columnar, key-value, and streaming patterns; ability to reason about trade-offs under specific performance and latency requirements
Proven track record delivering via Agile/Scrum methodologies
Experience leading legacy system modernization initiatives
Strong communication skills — ability to work effectively with both technical teams and non-technical business users
A constant learning and upskilling mindset
Fluency in AI/GenAI for engineering productivity (integration strategy, code review, test-case creation, and code generation), with a strong understanding of the evolving AI landscape and the ability to apply AI technologies effectively in business and technical contexts.

Nice To Haves

Experience in Financial Services, particularly portfolio performance calculations, NAV/returns, or risk metrics is a plus
Experience with PySpark for large-scale data processing
Infrastructure-as-Code experience, preferably Terraform
Experience with Snowflake as an analytical data warehouse
Microservices architecture and Serverless technologies
Experience with CI/CD pipelines and code quality tooling
Experience in C# and .NET software development is a plus

Responsibilities

Architect and lead development of a high-throughput, event-driven performance calculation engine on AWS, processing large volumes of financial data with accuracy and auditability requirements.
Drive the migration of the legacy performance reporting application stack onto a modern, cloud-native technology platform — defining migration strategy, sequencing, and risk mitigation.
Design scalable distributed systems using Python, Apache Kafka, PySpark, and AWS services (Lambda, Batch, Glue, Athena, S3, DynamoDB).
Define and enforce data modeling standards, schema design, and data structure patterns appropriate for performance calculation use cases.
Establish observability, alerting, and runbook standards to ensure system reliability and auditability.
Lead Agile-based delivery: sprint planning, backlog refinement, and iterative delivery cadences.
Provide flexible, pragmatic solutions to complex business problems within firm technology standards and regulatory constraints.
Author and review technical design documents, ADRs (Architecture Decision Records), and runbooks.
Own and enforce code quality standards; conduct code and merge-request reviews.
Build comprehensive test coverage: unit, integration, functional, and performance tests.
Research and evaluate open-source technologies and cloud-native AWS services; drive adoption where justified.
Mentor and lead a global team of engineers; provide regular feedback, support career development, and foster an inclusive, high-performing engineering culture.
Partner with business analysts and stakeholders to translate complex financial requirements into technical specifications.
Collaborate cross-functionally with architecture, data platform, and infrastructure teams.
Communicate technical trade-offs and roadmap recommendations clearly to senior leadership.