Senior Data Platform Engineer (AI / Data Fabric / Iceberg Lakehouse)Location: Boston, MA (Onsite 4 days/week)
About Our ClientOur client is a global investment firm building foundational
AI, data, and platform capabilities to enable scale and business transformation. Their platform organization is responsible for evolving technology into robust, reusable, platform-based solutions that increase agility and deliver material business impact across the firm.
The TeamYou'll join a core
AI, Data, and Platform Technologies engineering team that architects and supports the firm's foundational data and AI capabilities. This team is a key enabler for firm-wide services-designing platform primitives that power AI and investment workflows at enterprise scale.
The RoleOur client is hiring a
Senior Engineer to take a hands-on technical leadership role in Boston. You will help design and build world-class data engineering capabilities that process massive pipelines, leverage AI-powered insights and document extraction, and integrate across diverse cloud-powered databases.
You'll define the technical blueprint for how the firm
structures, stores, governs, and leverages data to support critical AI and investment platforms-ensuring integrity, performance, and accessibility at scale. This is an onsite role with expectations to be in the Boston office
4 days per week.
What You'll Do- Lead the architecture, buildout, and modernization of a unified data fabric, establishing scalable patterns for access, interoperability, governance, and productization across business and technology teams
- Own the design and evolution of Apache Iceberg-based data platform capabilities: ingestion/egress, replication, streaming, performance tuning, lifecycle management, and adoption standards for analytical + operational use cases
- Define and implement compute architecture across stateful, stateless, and distributed processing layers-balancing performance, resiliency, scalability, and cost
- Design and drive adoption of event-driven patterns for real-time ingestion and data movement with low-latency, reliable, observable flows
- Extend platform capabilities to support the firm's AI/ML ecosystem, including curated datasets, feature-ready pipelines, training/inference data services, and integration points for model development and deployment
- Translate business and engineering priorities into a clear technical roadmap-sequencing platform investments for long-term value
- Serve as a senior engineering lead across strategic platform domains, partnering with app engineering, enterprise architecture, data consumers, and ML stakeholders
- Establish standards for data quality, observability, lineage, governance, security, and operational excellence across batch and streaming environments
- Mentor junior engineers and raise the bar on design rigor, implementation quality, and operational ownership
- Evaluate emerging technologies, run PoCs, and recommend production-ready solutions aligned with target-state architecture
What Our Client Is Looking For- Bachelor's degree in CS/Engineering/IS (advanced degree preferred)
- 4+ years in data engineering, distributed systems, or platform engineering, operating at a senior technical leadership level
- Proven platform mindset: designed/delivered enterprise-scale data platforms or lakehouse ecosystems with emphasis on scalability, reliability, governance, and developer enablement
- Deep hands-on experience with Apache Iceberg and modern open table formats (modeling, partitioning, tuning, metadata management, operational best practices)
- Strong understanding of distributed compute architectures (stateful/stateless processing, orchestration, fault tolerance, performance optimization)
- Experience implementing event-driven/streaming architectures using modern messaging and data movement patterns
- Experience enabling AI/ML platform capabilities (pipeline design, feature/data prep, integration with model development or production ML systems)
- Strong proficiency in Python and SQL; Java/Scala and modern data processing frameworks highly desirable
- Cloud-native/containerized experience, including orchestration, infra automation, and observability tooling
- Ability to operate as a senior technical decision-maker: influence architecture, drive execution through others, and partner across technical + non-technical stakeholders
- Highly desirable: experience in AI Harness engineering
Why This Role- Own core architectural decisions for a firm-wide data fabric and lakehouse platform
- Work at the intersection of high-scale data engineering and AI enablement
- Build real-time and batch systems with strong governance, lineage, and production standards
- High visibility, high leverage platform work that compounds across many business units
Never miss an opportunity! Create an alert based on the job you applied for.
