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Job Description Role: Director - Analytics Products and Solutions Location: Bangalore (Hybrid) Role Type: People Leader (multi-team / product portfolio) Reporting to: COO What we are- MiQ We’re MiQ, a global programmatic media partner for marketers and agencies. Our people are at the heart of everything we do, so you will be too. No matter the role or the location, we’re all united in the vision to lead the programmatic industry and make it better. Role purpose As Director - Analytics Products and Solutions , you will be the technical leader who owns the end-to-end architecture, solutioning, and delivery of MiQ's local product portfolio. Product strategy, roadmap prioritisation, and go-to-market plans are owned by commercial product leadership; you will partner closely with them, contributing technical feasibility, architectural input, and solutioning expertise to shape what gets built. Your core accountability is for how products are built, tested, deployed, maintained, and evolved - spanning product architecture, scalability best practices, DevOps, QA and testing frameworks, adoption tracking, and Agile/Scrum delivery practices - ensuring world-class engineering practices and leveraging AI accelerators to ship high-quality solutions at speed. You will also maintain strong awareness of and hands-on familiarity with modern data and analytics tooling (Ex: Databricks, Spark, Gathr) to inform sound technology choices. As you help shape the strategy, prioritisation, and evolution of MiQ’s Local Products capability - in partnership with commercial product leadership - your core mandate is also to ensure Local Products builds the right capabilities - not just more capabilities - by: • Defining what Local Products should and should not build • Establishing clear ownership boundaries with Sigma (central product) • Driving prioritised, scalable, high-impact product development by integrating AI accelerators into the process • Shifting Local Products from a reactive build function to a structured, product-led capability layer This is a technical leadership and product governance role with deep technical depth, working in close partnership with commercial product leadership - who are accountable for product strategy, roadmap, and go-to-market plans. You will work at the intersection of: • Data Science organisation – partnering with the DS leadership to translate models and analytical capabilities into production-ready product features. • Local Product & Commercial teams – shaping products that drive measurable business outcomes for key markets. • Engineering & Platform teams – ensuring products are robust, scalable, well-tested, and cost-efficient. • Data & Analytics (DnA) – leveraging reusable data assets and analytical capabilities. What you'll do 1. Product Vision, Strategy, Identity & Roadmap Ownership • Define the role of Local Products within MiQ’s ecosystem: As the agency solutions layer (planning, activation, signal generation) Distinct from Sigma (scale layer) and Measurement & Insights • Clearly articulate: What LP builds What LP does NOT build How LP supports markets vs Product vs DnA • Partner with central Product teams to: transition scalable capabilities into Sigma avoid parallel / duplicate builds • Evolve LP from a feature factory to capability-driven organisation • Translate ambiguous business problems from markets into clear product hypotheses, technical problem statements, and prioritised roadmaps to solve them. • Prioritise across multiple products and initiatives using impact, effort, and strategic alignment frameworks (Ex: RICE, MoSCoW, Cost of Delay); ensure product and solution OKRs are met across the portfolio. • Own the product lifecycle end-to-end - from ideation and proof-of-concept through build, launch, adoption tracking, iteration, maintenance, and sunset decisions. • Make deliberate build vs buy vs partner decisions - evaluating technology options, open-source components, and third-party integrations against in-house development for each product capability. • Partner with Product Management and commercial stakeholders to validate opportunities and translate market needs into technically sound, deliverable product plans. 2. Technical Leadership & Solutioning • Provide hands-on technical leadership across solutioning and product architecture - designing systems that are robust, extensible, and built to scale across markets, in line with scalability best practices. • Champion DevOps practices - CI/CD pipelines, infrastructure automation, environment management, and release orchestration - to enable fast, reliable, and safe deployments. • Own QA and testing frameworks across the portfolio - defining automated testing strategy, coverage standards, and quality gates that products must clear before release. • Drive adoption tracking and instrumentation - ensuring every product has clear usage, engagement, and adoption metrics built in from day one. • Bring strong Scrum ceremonies expertise and best practices - leading and coaching teams through sprint planning, stand-ups, backlog grooming, sprint reviews, and retrospectives to drive predictable, high-quality delivery. • Maintain strong awareness of and evaluate the latest data and analytics tooling - including Databricks, Spark, Gathr, and other emerging platforms - to inform build decisions and keep the technology stack current. 3. Prioritisation and Product Governance • Establish a centralised intake and prioritisation model across markets • Ensure all work is evaluated against: commercial impact Scalability Reusability Sigma alignment • Act as the single-threaded owner of roadmap decisions and deployment excellence, making trade-offs across: market demand engineering capacity strategic priorities • Reduce: ad-hoc builds Duplication low-impact features • Provide technical leadership across the full (SDLC): requirements analysis, system design, implementation, testing, deployment, monitoring, and ongoing maintenance. • Establish and own the QA/QC framework for the portfolio: automated testing strategies (unit, integration, regression, performance), test coverage standards, and quality gates that products must clear before release. • Own the maintenance and upgrade strategy for shipped products - including SLA definitions, incident management, technical debt tracking and upgrade pathways that keep products healthy and supportable over time. • Champion the integration of AI accelerators into the product development workflow - evaluating and embedding tools such as AI-powered code assistants (Ex: Copilot, Cursor), automated code review, AI-driven test generation, intelligent documentation, and GenAI-powered prototyping to boost developer productivity and reduce cycle time. • Partner with the Data Science organisation to productionise models and analytical capabilities - defining clear contracts, integration patterns, performance benchmarks, and monitoring for ML components within products. • Drive design thinking and user-centric development practices - ensuring local products are built with deep empathy for end-user workflows, not just technical elegance. 4. People Leadership, Coaching & Culture • Lead and grow a high-performing product + technical team • Build leaders who can: think commercially prioritise effectively operate cross-functionally • Shift team mindset from: “delivering requests” to “solving problems at scale” • Build a high-trust culture that emphasises ownership, quality craftsmanship, delivery excellence, learning, and autonomy. • Coach technical leaders on stakeholder management, storytelling, product thinking, and commercial awareness so they can independently drive workstreams and influence senior partners. • Foster cross-functional fluency - developing team members who are equally comfortable discussing system architecture, product metrics, and business impact. • Upskill teams on modern development practices and AI-powered tooling - ensuring the organisation stays current with evolving best practices • Define and support learning and development plans, including opportunities to contribute to thought leadership (blogs, talks, open-source contributions, internal workshops). 5. Cross-Functional Collaboration & Stakeholder Management • Partner with: Product (Sigma) Product Data Science Engineering Markets & Commercial • Drive alignment across: Roadmap Ownership delivery expectations • Act as the primary technical product partner for local Product, Commercial, Markets, and Strategy leaders on your products. • Partner with key stakeholders - aligning on model requirements, productionisation timelines, performance targets, and integration roadmaps for ML-powered features. • Drive cross-functional alignment - facilitate product councils, architecture reviews, roadmap syncs, and sprint demos to ensure all teams are rowing in the same direction. • Communicate complex technical concepts in simple, business-friendly language to senior, non-technical stakeholders - building confidence, driving adoption, and securing buy-in for investment decisions. • Represent DnA and MiQ in internal and external forums (Ex: product councils, client meetings, industry events) as a senior technical product leader. 6. Cost, Risk & Operational Excellence • Own compute and tooling budgets for your domain; drive optimisation initiatives without compromising quality or innovation. • Champion effective, lightweight Agile practices across teams; partner with Program/Project Management to continuously improve ways of working and delivery predictability. • Proactively identify delivery, technical, and organisational risks and put in place mitigation plans • Establish product health dashboards - tracking adoption, engagement, client satisfaction, and business impact metrics for every product in the portfolio. 7. Org-wide Initiatives & Thought Leadership • Contribute meaningfully to org-wide initiatives (Ex: hiring, calibration, promotion frameworks, diversity & inclusion, capability building) beyond your immediate remit. • Help define MiQ's long-term product development and AI strategy, including the adoption of AI accelerators, next-generation development practices, and emerging technology evaluation. • Champion a product-led mindset across the organisation - advocating for quality-first delivery, user-centricity, and continuous improvement as cultural norms. • Proactively contact new and existing clients and educate, propose and secure buy-in on MiQ Solutions Who are your stakeholders? You will work closely with: • Product Data Science organisation : as a key stakeholder and partner, collaborating on model productionisation, ML feature integration, and analytical capability roadmaps. • Data & Analytics leadership : to shape strategy, investment, and talent plans. • Product Management (global and local) : to co-own roadmaps and outcomes for local products. • Engineering & Platform teams : to build robust, scalable, and maintainable systems and shared infrastructure. • Design & UX : to ensure products are intuitive, usable, and aligned with end-user workflows. • Markets & Commercial teams (Sales, Trading, Account Management, Solutions, Client Partners): to validate opportunities, understand market needs, and drive client value at scale. What you’ll bring • 12+ years in product, platform, or technical leadership roles in data-heavy environments (adtech/martech preferred) • Proven experience: defining product strategy and roadmaps prioritising across competing demands scaling products from 0->1 and 1->N • Experience working across: product engineering data science commercial teams • Comfortable making trade-offs across: scale vs custom speed vs quality market vs product • Ability to connect: Capabilities Workflows platforms (Sigma) • Strong understanding of: data platforms (Databricks, AWS) engineering practices ML/DS productionisation Enough to challeng