Data Engineer- Infrastructure

Kforce's client, a leading global investment firm is seeking a Data Engineer, Infrastructure to join its core engineering team in Boston, MA. Summary: This is a high-impact technical leadership role focused on building elite data infrastructure to power advanced AI and investment platforms. You will design world-class pipelines that process massive financial datasets, integrate AI-driven document extraction, and bridge diverse cloud-native databases. In this role, you will define the blueprint for how the firm structures and leverages data, ensuring high performance, integrity, and accessibility for mission-critical services. Key Responsibilities:

• Architect and modernize a unified data fabric, setting standards for data access, governance, and productization across the enterprise
• Lead the evolution of an Iceberg-based lakehouse, overseeing ingestion, streaming, replication, and lifecycle management
• Define the compute architecture across stateful and distributed layers, balancing scalability with cost efficiency
• Implement event-driven patterns to ensure low-latency, observable data flows for real-time system integration
• Expand platform capabilities to support AI/ML, including feature-ready pipelines and scalable services for model training and inference
• Convert business priorities into a technical roadmap, making critical architecture decisions that maximize long-term platform value
• Partner with application teams and stakeholders to serve as the lead authority for strategic data domains
• Enforce high engineering standards for data quality, lineage, security, and operational excellence
• Mentor junior talent, fostering a culture of design rigor and implementation quality
• Conduct R&D on emerging technologies to recommend production-ready solutions for the firm's target architecture
• Degree in Computer Science, Engineering, or a related field; Advanced degree preferred
• 4+ years in data or platform engineering, with a track record of senior-level technical leadership
• A "platform-first" mindset with experience delivering enterprise-scale lakehouse ecosystems
• Deep expertise in Apache Iceberg and open table formats, including partitioning and performance tuning
• Strong grasp of distributed compute models, workload orchestration, and fault-tolerant system design
• Proven success implementing streaming architectures and modern messaging patterns
• Experience building data services that support AI/ML workflows and production model deployments
• Advanced proficiency in Python and SQL; Java or Scala skills are a major plus
• Familiarity with cloud-native/containerized environments and infrastructure automation
• Excellent communication skills with the ability to influence technical and non-technical stakeholders
• Exposure to large-scale AI orchestration frameworks is highly desirable