Senior Data Engineer

Staff Data Platform Engineer (AI / Data Fabric / Iceberg Lakehouse)

Location: Boston, MA (Onsite 4 days/week)
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About Our Client

Our 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 Team

You'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 Role

Our 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)
• 8+ 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