Apprentice Data Solutions Engineer Jobs (NOW HIRING)

Mid to Staff Engineer, Enterprise Data Exchange & Agentic Analytics (Data Explorer)

Location: Boston, MA (Onsite 4 days/week)
Contact / Apply: Aidan@nxtlevel.io

About Our Client

Our client is building foundational AI, data, and platform capabilities that enable global scale and business transformation. Their platform engineering organization is responsible for architecting robust, reusable solutions that improve agility and deliver material business impact across a complex, multi-business enterprise.

The Role

Our client is hiring a Mid to Staff Engineer to join a core AI/Data/Platform engineering team in Boston. This is a pivotal role focused on defining the enterprise strategy and target-state architecture for an internal “enterprise data exchange” capability (referred to in the posting as Data Explorer).

This role blends data platform architecture, analytics modernization, workflow orchestration, and agentic/AI-enabled analytics. You'll set long-term direction, drive cross-functional transformations, and serve as a senior technical authority influencing multiple platforms, teams, and business functions. Onsite expectations: 4 days/week in Boston.

What You'll Own

• Enterprise Data Exchange Strategy (Data Explorer): Define the target-state architecture for governed, intuitive data discovery, access, sharing, and reuse across the organization
• Metadata + Governance Foundations: Establish standards for metadata strategy, semantic consistency, entitlements, lineage, interoperability, and trusted data product consumption
• Agentic Analytics Enablement: Act as senior technical authority for analyst agents—designing governed, explainable, auditable patterns that improve analyst productivity and decision support
• Workflow Orchestration Patterns: Drive reusable control patterns for workflow orchestration across business domains (scalable, resilient, transparent, measurable)
• BI Rationalization Roadmap: Own the strategy to reduce fragmentation across BI tools, metrics, dashboards, and user experiences; standardize KPI definitions and semantic layers

What You'll Do

• Lead design and implementation of enterprise data solutions supporting analytics, operational workflows, data sharing, and agent-enabled analytics
• Drive cross-functional modernization efforts: KPI harmonization, reporting standardization, platform usage models, governance, adoption, and cost efficiency
• Partner with senior engineering, architecture, analytics, product, and business leaders to prioritize investments and resolve complex cross-platform issues
• Mentor senior engineers and technical leaders—raising the bar for platform thinking and enterprise-scale execution
• Evaluate emerging technologies across analytics, workflow automation, agentic systems, and enterprise data platforms and translate them into actionable architectural direction
• Serve as a trusted advisor on complex initiatives spanning multiple teams and platforms, with accountability for shaping decisions and driving change

What Our Client Is Looking For

• Bachelor's degree in CS/Engineering/IS or related; advanced degree preferred
• 5+ years in data platforms, analytics engineering, enterprise architecture, workflow/process tech, or intelligent automation, operating as a senior enterprise technical leader
• Proven track record defining and delivering enterprise platform strategy/architecture across multiple domains and influencing outcomes in large, matrixed orgs
• Deep experience with enterprise data exchange / catalog / marketplace / self-service data platforms (metadata, governance, lineage, access controls, interoperability, adoption at scale)
• Demonstrated expertise in AI-enabled analytics and agentic systems, with governed, explainable, auditable patterns
• Strong experience modernizing BPM/workflow orchestration capabilities and understanding how controls + automation + data platforms work together
• Proven success leading BI modernization and rationalization (consolidation, semantic standardization, KPI harmonization, reporting transformation)
• Strong proficiency in SQL and Python; broad fluency across analytics platforms, data architecture, workflow tech, and integration patterns
• Executive-level communication and influencing skills; ability to align senior stakeholders and drive change across boundaries
• Ability to mentor senior talent and elevate architecture rigor across a broad engineering organization

Why This Role

• Enterprise-scale ownership over the strategy for data discovery, sharing, governance, and adoption
• High-leverage intersection of data platforms + BI modernization + workflow orchestration + agentic analytics
• A seat where your architecture decisions will influence multiple platforms and business functions—not just one team's codebase