Senior Data Architect – Pre-sales, Solutions

Endava

. Serve as a senior trusted advisor to CIO, CTO, CDO, CRO, business, product, and technology stakeholders .

Posted 9/15/2026full-timeRemote • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Architecture, Machine Learning, and AI solutions, with a strong focus on translating complex business problems into actionable insights. Proven ability to lead multidisciplinary teams and communicate effectively with executive stakeholders while ensuring rigorous model development and validation practices.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyData ArchitectureMachine Learning ExpertiseExecutive Communication

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Hard Skills

ForecastingMultivariable RegressionCollinearity AnalysisModel TuningStatistical SignificanceData Leakage PreventionMetric FluencyHierarchical ModelingMLOpsLarge-Scale Categorical Encoding

Soft Skills

Client ConsultingThought LeadershipTeam MentoringCommunicationCommercial Judgment

Tools & Technologies

SnowflakeGitData PlatformsAPIsNotebooks

Industry Keywords

Sports AnalyticsMedia AnalyticsEntertainment AnalyticsSponsorshipRevenue Intelligence

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Serve as a senior trusted advisor to CIO, CTO, CDO, CRO, business, product, and technology stakeholders
Lead Data & AI discovery and translate ambiguous business problems into measurable, production-ready solutions
Design end-to-end architectures spanning data platforms, analytics, machine learning, GenAI, applications, APIs, governance, and integrations
Lead and challenge advanced forecasting and predictive-modeling approaches
Define business and model success measures, including R², WAPE, MAPE, statistical significance, and business-impact KPIs
Ensure point-in-time correctness, prevent data leakage, and maintain rigorous model-development and validation practices
Provide hands-on technical leadership using Python, SQL, Snowflake, notebooks, Git, and modern Data/AI platforms
Shape AI use cases across forecasting, sponsorship sales, lead scoring, next-best-action, revenue intelligence, personalization, subscription growth, and commercial optimization
Evaluate whether classical analytics/ML, GenAI, or agentic AI is the appropriate solution
Lead architecture and solution-design workshops and present recommendations to senior and executive audiences
Support proposals, SOWs, RFI/RFP responses, estimates, staffing models, and technical solution shaping
Lead and mentor multidisciplinary teams across Data Science, Data Engineering, AI Engineering, Software Engineering, and Architecture
Participate in client stand-ups, backlog refinement, executive readouts, and strategic planning
Teach and transfer knowledge to client teams; ensure documentation, reproducibility, and handover
Challenge client requests when the proposed approach does not solve the underlying business problem
Participate in internal and external meetings via video calls, as necessary

Requirements

What you’ll need

5+ years of applied forecasting and data domain experience
Proven experience leading at least two comparable forecasting engagements from discovery through production/handover
Strong experience with comparable-unit / same-store-style forecasting approaches
Expert-level multivariable regression, collinearity analysis, VIF interpretation, model tuning, selection, and holdout validation
Strong understanding of sparse and zero-inflated datasets; must understand why nulls cannot be silently treated as zero
Strong metric fluency, including R², WAPE, MAPE, and p-values
Deep understanding of data leakage and point-in-time feature correctness
Strong Python and SQL skills and experience creating reproducible analytical workflows/notebooks
Git and pull-request-based software delivery experience
Strong Data Architecture and Solution Architecture capability across ingestion, transformation, modeling, security, governance, APIs, cloud, and production operations
Strong understanding of ML, GenAI/LLMs, RAG, AI agents, and modern enterprise AI patterns
Proven executive communication skills, including presenting to non-statistical audiences using business outcomes first and methodology second
Ability to communicate forecast/model limitations, uncertainty, and risk in plain language
Proven client consulting and thought-leadership experience; able to teach methodology, not simply execute it
Experience leading senior client workshops, technical discovery, architecture discussions, and executive readouts
Strong commercial judgment and ability to connect technical decisions to revenue, operational, or customer outcomes
Preferred domain experience in sports, media, entertainment, streaming, ticketing, subscriptions, sponsorship, advertising, telecom, or commercial/revenue analytics
Desired experience with hierarchical/mixed-effects modeling, ADRs, large-scale categorical encoding, MLOps, governance, and responsible AI
Strong Snowflake experience; Snowflake ML / Model Registry experience
10–12+ years overall Data, Analytics, AI, Architecture, or related technology experience
Ability to go into corporate or client offices to work onsite, as necessary
For positions requiring business travel and/or event attendance, a valid driver’s license and acceptable driving record are required

Benefits

Comp & perks

Robust healthcare and benefits including Medical, Dental, vision, Disability coverage, and various other benefit options
Flexible Spending Accounts (Medical, Transit, and Dependent Care)
Employer Paid Life Insurance and AD&D Coverages
Health Savings account paired with our low-cost High Deductible Medical Plan
401(k) Safe Harbor Retirement plan with employer match with immediately vest
Reasonable accommodations during the recruitment process, if requested