Director, Data Strategy – Engineering

Portage Point Partners

. Define and own the firm’s data platform strategy for the India delivery organization, spanning cloud data architecture, AI data infrastructure, master data management and the analytics capability roadmap .

Posted 4/20/2026full-timeGurgaon • 🇮🇳 IndiaLeadWebsite

Tech Stack

Tools & technologies

CloudERPETL

About the role

Key responsibilities & impact

Define and own the firm’s data platform strategy for the India delivery organization, spanning cloud data architecture, AI data infrastructure, master data management and the analytics capability roadmap
Drive architectural decisions for the firm’s data ecosystem including data lakehouse design (bronze/silver/gold medallion architecture), real-time versus batch processing trade-offs, semantic layer strategy, data mesh adoption and AI-ready data product frameworks
Own the data architecture review function, ensuring all new AI products and data pipelines meet architectural, security and governance standards before development commences
Execute the data strategy that enables the AI Solutions product roadmap, defining how data is structured, labeled, versioned and served to AI/ML models across consulting use cases including CDD/FDD automation, value creation tracking, working capital optimization, restructuring scenario engines, portfolio benchmarking and MIS intelligence layers
Drive the development of the firm’s proprietary financial and industry data assets including training data curation, golden datasets for model evaluation and benchmarking databases
Design the firm’s knowledge graph strategy, capturing structured relationships between companies, deal comparables, management teams and operational KPIs to power next-generation AI reasoning
Oversee design and operation of scalable ELT/ETL pipelines ingesting structured and unstructured data from diverse sources including financial data providers (Capital IQ, Refinitiv, PitchBook, Bloomberg), client ERP/CRM systems, SEC filings, management packs and market research
Own the analytics engineering layer powering consulting analytics including financial benchmarking, working capital KPI dashboards, EBITDA bridge models and cost structure analyses, and build reusable data product templates that let consulting teams rapidly spin up client-specific analytics environments
Lead and develop a team of two to three Vice Presidents and their Senior Associates (approximately 15 to 20 professionals) across data engineering, analytics engineering and data governance, providing strategic and technical direction, conducting structured performance reviews and owning career development
Drive talent strategy for the Data Strategy & Engineering function including hiring plans, role design, vendor partner selection and management, capability building, career ladders and compensation benchmarking in partnership with HR
Drive the data governance framework including policies, standards, stewardship model and compliance controls for handling client deal data, portfolio company data and third-party data, in alignment with NDA and regulatory obligations
Oversee data security architecture in collaboration with the security function, with particular attention to AI training data handling, model output retention and deal data segregation
Build and operate data quality programs including automated monitoring, anomaly detection and alerting to surface data issues before they affect AI model outputs or consulting deliverables
Partner with the India Delivery Leader, the Director, AI Solutions and US-based Practice Line Leaders to translate firm priorities into a sequenced data platform roadmap with measurable business outcomes, and report on platform-level KPIs including adoption, data quality, freshness SLAs, productivity impact and ROI
Identify and shape data monetization opportunities within the firm’s consulting practice including proprietary benchmarking databases, index products and data-as-a-service offerings, and partner with firm leadership to commercialize proprietary data assets as consulting IP and competitive differentiators
Serve as a thought leader on data strategy in deal advisory and portfolio management, engaging in senior client conversations on data room analytics, portfolio data standardization and data-driven value creation, and representing the firm at internal forums and external industry events where appropriate
Manage relationships with third-party data providers, evaluate new data sources for relevance to consulting use cases and lead the evaluation and adoption of emerging data technologies including data mesh, federated query engines and AI-native data platforms
Contribute selectively as a hands-on technical leader on flagship initiatives where senior architectural judgment is required
Lead firm-wide knowledge sharing, training and change management efforts to scale data and analytics capability across practice lines
Support business development by shaping data-related proposals, client presentations and solution demonstrations
Support internal trainings and best practice sharing
Contribute to a high-performing, inclusive and values-driven culture

Requirements

What you’ll need

Bachelor’s of Technology / Engineering and / or Master's in Computer Science, Data Engineering, Information Systems, Statistics or related technical field from a top undergraduate program; MBA with quantitative focus strongly preferred
Willing to relocate to or be primarily present in Gurgaon
Ability to collaborate across global time zones, including US-based teams
Ten to fifteen years of progressive experience in AI/ML, software engineering or related technical disciplines, with a meaningful portion of that experience in management consulting, professional services or private equity-backed advisory environments
Demonstrated experience leading AI or technology functions of 10 or more professionals, including managing managers and developing senior individual contributors
Proven track record setting product or portfolio roadmaps for AI, data or software functions and translating ambiguous business priorities into sequenced delivery plans
Track record building and scaling teams, including direct hiring leadership and experience managing vendor or offshore delivery partners
Deep working knowledge of LLM-powered applications, agentic AI architectures, automation workflows and the modern AI tooling ecosystem (e.g., OpenAI, Claude, LangChain, N8N, Zapier or similar)
Proficiency with AI coding tools such as Claude Code and the ability to engage credibly in technical reviews and architectural decisions
Strong understanding of data engineering, model evaluation, MLOps and modern software development practices
Demonstrated ability to establish and enforce responsible AI standards including bias detection, explainability and data privacy across production AI systems
Experience operating in client-facing or executive-facing settings with the ability to shape AI-related proposals, presentations and senior stakeholder conversations
Superior written and verbal communication skills, including executive-ready presentation and reporting skills
Proven ability to thrive in lean, fast-moving teams
High attention to detail, responsiveness and ownership mindset
Track record of success in high-pressure environments
Ability to convey technical concepts to non-technical stakeholders.

Benefits

Comp & perks

Health insurance
Paid time off
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data architectureAI data infrastructuremaster data managementdata lakehouse designELTETLdata governanceMLOpsdata engineeringanalytics engineering

Soft Skills

leadershipcollaborationcommunicationstrategic directionperformance reviewscareer developmentproblem-solvingattention to detailownership mindsetadaptability

Certifications

Bachelor’s of TechnologyMaster's in Computer ScienceMBA with quantitative focus