Data Engineer

Kforce has a client in NYC that is seeking a Data Engineer to join a core engineering squad within our enterprise technology division. This hands-on role requires deep technical knowledge in enterprise data architecture and a proven history of processing highly sophisticated, large-scale transaction datasets. You will spearhead the creation of robust data pipelines, incorporate advanced automated analytics and document processing tools, and link multi-cloud data environments. This position operates on-site at our regional office on a hybrid schedule.

Core Responsibilities:

• Unified Framework Architecture: Oversee the design, construction, and modernization of our centralized data network, establishing repeatable methodologies for information access, governance, and delivery across internal departments
• Modern Lakehouse Formats: Direct the evolution of our lakehouse storage framework, overseeing ingestion, data delivery, replication, stream management, speed tuning, and standard lifecycle procedures for both reporting and production environments
• Distributed Computing: Formulate the system processing strategy across stateful, stateless, and clustered computing environments
• Real-Time Streaming: Architect and promote message-based, real-time messaging patterns for immediate information ingestion and cross-system connection
• Strategic Planning: Convert business needs into clear technical milestones
• Cross-Functional Leadership: Direct technical strategy across critical platform domains.Engineering Rigor: Standardize operational frameworks for data verification, tracing, compliance, and monitoring
• Technical Mentorship: Guide developing engineers, elevating development standards regarding design validation, code quality, and technical accountability* Education: Technical degree in a relevant field like Software Engineering, Computer Science, or equivalent practical experience
• Experience: 4+ years of experience navigating enterprise database design, clustered computing, or infrastructure orchestration, with clear tenure operating in an influential technical capacity
• Mindset: An infrastructure-first mindset with a history of delivering high-capacity storage ecosystems focused on developer productivity and data tracking
• Table Formats: Comprehensive hands-on deployment of modern open-source table formats (such as Iceberg or Delta), including storage partition strategies, metadata oversight, and performance optimization
• Compute Engines: Deep knowledge of clustered compute engines, workflow orchestration tools, system recovery, and computational tuning
• Messaging: Proven implementation of asynchronous communication models using modern broker networks and messaging flows
• Analytics: Experience optimizing data ecosystems for production analytics, including specialized pipeline building and model deployment workflows
• Languages: Professional fluency in scripting languages (such as Python and SQL); Familiarity with object-oriented languages (like Java or Scala) and enterprise processing tools is a strong plus
• DevOps Tools: Competency working with cloud-managed containerization tools, infrastructure-as-code automation, and centralized system monitoring software
• Leadership: Ability to direct high-stakes architectural choices, influence engineering directions, and bridge communication gaps between technical teams and business directors
• Communication: Excellent presentation skills, with a capability to explain complicated cloud infrastructure concepts to non-technical partners