• Lead the technical delivery of implementations and major client initiatives: discovery, solution design, execution plan, and delivery. • Own end-to-end data modeling strategy (dimensional models, semantic consistency, performance, and extensibility). • Enforce engineering standards in client codebases: PR discipline, test strategy, documentation, release management, and automation. • Diagnose and resolve complex data quality issues; quantify downstream impact and drive remediation plans with clients and internal teams. • Serve as a senior client-facing technical consultant: run technical workshops, present findings, propose options/tradeoffs, and influence stakeholder decisions. • Build reusable accelerators (templates, reference models, validation suites, playbooks) that improve delivery speed and consistency across clients. • Mentor and upskill Client Engineers (including Level 1 and Level 2) through pairing, reviews, and coaching. • Partner cross-functionally (Product, Platform Engineering, Client Success, Security/Compliance) to improve platform capabilities and delivery practices. • Champion responsible for AI usage in engineering workflows: define guardrails, review standards, and quality checks for AI-assisted code and analysis.