Senior Engineer, Data Platform - AR

NxT Level•Boston, MA

3d•Onsite

About The Position

Our client is hiring a Software Engineer to join a core Data Platform Engineering team focused on data distribution, governed data access, and AI-powered data intelligence. This team owns a primary governed data exchange platform that is evolving from an internal data catalog into a unified interface for discovering and accessing structured data products, AI-powered document analysis, business intelligence assets, and secure external client data. This is a hands-on senior engineering role for someone who can build across modern web applications, backend services, cloud data platforms, identity and access controls, AI-enabled user experiences, and BI integrations. The right candidate will be comfortable owning complex technical work, partnering with senior engineers and platform leaders, and helping deliver secure, scalable, enterprise-grade data products in a highly regulated environment.

Requirements

Senior-level software engineering experience building user-facing data platforms, enterprise web applications, or complex products at scale
Strong full-stack engineering skills, including modern React, TypeScript, and backend API or service-layer development
Experience building over cloud-based data platforms
Experience with Snowflake, lakehouse architectures, Apache Iceberg, AWS, or similar technologies
Strong understanding of enterprise identity and access management
Experience with SSO, RBAC, ABAC, entitlement models, or identity governance integrations
Experience building secure internal or external-facing access patterns
Hands-on experience with AI-powered product capabilities, such as LLM integration, retrieval over structured and unstructured data, natural language query interfaces, AI-assisted document analysis, or enterprise agent platforms
Experience integrating BI tools such as Sigma, Power BI, Tableau, or similar platforms
Strong SQL and Python skills
Ability to work across application, data, integration, and AI technology layers
Strong engineering judgment with the ability to build secure, scalable, reliable, observable systems
Clear communication skills across engineering, product, operations, architecture, and business stakeholders

Nice To Haves

Experience in financial services or another highly regulated industry
Familiarity with SOX-aligned controls, auditability, data classification, and governed access to sensitive information
Experience with event-driven architectures and technologies such as Kafka
Familiarity with enterprise data products, data catalogs, data marketplaces, semantic layers, metadata management, lineage, and governed self-service data access
Experience modernizing or consolidating enterprise BI and reporting ecosystems
Experience partnering with product, operations, or business teams where engineering owns technical design and implementation

Responsibilities

Build and enhance a governed enterprise data exchange platform used across the firm
Develop modern full-stack applications using React, TypeScript, backend services, APIs, and cloud data integrations
Support the evolution of the platform from a data catalog into a broader governed data access and intelligence experience
Build user-facing experiences for structured data products, AI-powered document analysis, BI assets, and secure external data access
Help design and implement secure external client access patterns, including authentication flows, entitlements, and simplified user experiences
Build AI-powered data solutions, including governed Data Rooms, indexed document repositories, and structured data access experiences
Deliver natural language and chat-based experiences that allow users to query structured and unstructured data
Integrate data experiences with enterprise AI platforms, agent marketplaces, and internal analytics tools
Support BI consolidation efforts through integrations with tools such as Sigma, Power BI, or similar platforms
Partner with data engineering, data operations, product, architecture, analytics, and business stakeholders
Build reusable patterns for APIs, authentication, authorization, data access, AI integration, observability, testing, deployment, and operational support
Ensure systems meet enterprise expectations for security, reliability, performance, scalability, auditability, data classification, and regulatory controls
Participate in architecture discussions, technical design reviews, implementation planning, and engineering quality improvements