Client Principal, Data Analytics and AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Drive executive discovery sessions, envisioning initiatives, assessments, and workshops.

• Convert unclear business challenges into prioritized use cases, data products, and measurable results.

• Establish strong relationships across business, data, application, security, and cloud teams.

• Collaborate with account teams on opportunity assessment and account strategy development.

• Design comprehensive architectures encompassing ingestion, integration, storage, transformation, governance, analytics, ML, and GenAI.

• Develop proposals and Statements of Work (SOWs) detailing scope, assumptions, staffing, estimates, risks, and dependencies.

• Ensure that proposed solutions are feasible, secure, supportable, aligned with outcomes, and ready for implementation.

• Shape roadmaps for database, data platform, and cloud modernization in partnership with hyperscaler and technology collaborators.

• Provide architectural guidance through discovery, proof-of-value initiatives, pilot programs, and initial implementations.

• Mitigate technical risks and facilitate the transition from presales to delivery.

• Document results, assumptions, decisions, estimates, and acceptance criteria thoroughly.

• Recommend analytics, ML, AI, or GenAI solutions, including RAG, agents, grounding, evaluation, and guardrails.

• Implement data governance, cataloging, lineage, quality, and security-by-design practices.

⛳️ Requirements

• Over 15 years of experience in data, analytics, software engineering, cloud architecture, consulting, or a related domain.

• Extensive client-facing technical presales experience as an architect, principal consultant, or senior solution leader.

• Proven leadership experience in customer implementation and technical delivery.

• Demonstrated capability to lead executive workshops, define solutions, draft proposals and SOWs, and estimate project delivery timelines.

• Proficient in ETL/ELT patterns across batch, streaming, and event-driven pipelines, as well as lakehouse and modern warehouse concepts.

• Experience in modeling for operational, analytical, semantic, and AI workloads, including database modernization or platform migration.

• Knowledge of enterprise BI, semantic modeling, and the ML lifecycle/MLOps.

• Familiarity with RAG, agents, grounding, evaluation, guardrails, and responsible AI practices.

• Ability to provide guidance across AWS, Azure, and Google Cloud, selecting services based on client requirements.

• Fluency in data governance, cataloging, lineage, quality, and security-by-design principles.

• Understanding of project scope, scheduling, staffing, assumptions, dependencies, risks, margins, and delivery feasibility.

• In-depth expertise in one modern data platform and practical experience in another; ability to advise on Snowflake, Databricks, and Microsoft Fabric.

• Preferred qualifications include relevant data platform or cloud certifications and established partner relationships that support joint go-to-market efforts.

• Experience in adapting data and AI patterns to various industries, regulatory frameworks, and operational environments is preferred.

• Prior software or full-stack engineering experience is preferred.

• Experience in creating accelerators, assessment methodologies, reference architectures, or presales tools is preferred.

• Familiarity with AI-assisted engineering and delivery tools, ensuring sound human review, security, IP, and governance practices is preferred.

• Participation in conferences, publication of articles, or contributions to the community on modern data platforms and responsible AI is preferred.

🏝️ Benefits

• Travel requirement is less than 25%.

• Commitment to being an Equal Opportunity Employer.

• Provision of reasonable accommodations for individuals with disabilities.

• Strong commitment to fostering a diverse and inclusive workplace.