Key Responsibilities
- Data Strategy and Leadership
* Define and execute oneD’s data strategy in alignment with its product and business objectives.
* Develop a roadmap covering data infrastructure, analytics, BI, governance, experimentation, and audience intelligence.
* Establish clear ownership and accountability for data across the organization.
* Lead, coach, and develop the Data Engineering, Analytics, BI, and SEO teams.
* Prioritize data initiatives based on business impact, urgency, technical effort, and available resources.
* Communicate data insights, risks, and recommendations clearly to senior management.
- Data Platform and Engineering
* Oversee the development and maintenance of scalable data pipelines, warehouses, and analytical datasets.
* Integrate data from oneD’s mobile, web, tablet, Smart TV, video, advertising, subscription, payment, CRM, and marketing platforms.
* Ensure reliable collection of user behaviour, playback, content, advertising, and commercial data.
* Establish monitoring and alerts for pipeline failures, missing data, unusual changes, and delayed processing.
* Improve the reliability, performance, scalability, and cost efficiency of the data platform.
* Ensure data architecture can support future personalisation, recommendation, customer segmentation, and machine-learning use cases.
- Data Quality and Governance
* Establish a single source of truth for oneD’s critical business and product metrics.
* Define standard calculations for metrics such as MAU, DAU, watch time, unique viewers, content completion, retention, churn, subscription conversion, and advertising performance.
* Implement data-quality controls covering accuracy, completeness, consistency, timeliness, and duplication.
* Define data ownership, access permissions, documentation, retention policies, and governance standards.
* Ensure customer and behavioural data is managed securely and in accordance with applicable privacy requirements.
* Lead investigations into discrepancies between dashboards, platforms, and departmental reports.
- Analytics and Business Intelligence
* Deliver reliable dashboards, reporting, and actionable insights for management and business teams.
* Support analysis of audience acquisition, engagement, retention, churn, monetisation, and customer lifetime value.
* Provide insights into content performance, including reach, watch time, completion, audience segments, and contribution to retention or subscription.
* Analyse user journeys and identify points of friction in registration, login, playback, advertising, payment, and subscription conversion.
* Establish self-service reporting while maintaining consistent definitions and controlled access.
* Move the organisation from descriptive reporting toward predictive and prescriptive insights.
* Ensure analysis leads to clear recommendations and measurable actions.
- Product Analytics and Experimentation
* Partner with Product and Engineering to define tracking requirements before new features are developed.
* Ensure consistent analytics implementation across iOS, Android, web, tablet, and Smart TV platforms.
* Create measurement frameworks and success criteria for product launches and improvements.
* Establish an experimentation framework for A/B testing and other controlled tests.
* Evaluate whether product changes create measurable improvements in engagement, retention, conversion, or revenue.
* Work with QA to verify the accuracy of analytics events before releases.
- Audience Growth and SEO
* Oversee data-driven SEO measurement and performance in partnership with Product, Content, and Marketing.
* Improve the discoverability of oneD content across search engines and relevant digital channels.
* Monitor organic traffic, search rankings, click-through rates, indexing, and conversion from organic audiences.
* Ensure SEO priorities are supported by reliable data and aligned with broader audience-growth objectives.
* Identify valuable audience segments and opportunities for acquisition, re-engagement, and conversion.
- Stakeholder and Vendor Management
* Translate business questions into clear analytical and technical requirements.
* Work with external vendors and development partners to ensure correct data integration and implementation.
* Evaluate third-party analytics, BI, customer-data, attribution, and data-platform tools.
* Manage data-related budgets, vendor performance, implementation quality, and service levels.
* Ensure important technical knowledge, documentation, and data ownership remain within oneD.
Qualifications
* Bachelor’s or master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Economics, or a related discipline.
* At least 8–10 years of experience in data engineering, analytics, BI, data science, or related fields.
* At least 3–5 years of experience leading multidisciplinary data teams.
* Strong understanding of data engineering, analytics, BI, governance, and cloud data architecture.
* Advanced knowledge of SQL and a working understanding of Python or similar languages.
* Experience with data warehouses, data lakes, ETL/ELT pipelines, APIs, dashboards, and event-based analytics.
* Proven ability to translate complex data into clear commercial and product recommendations.
* Experience establishing common metric definitions and resolving data-quality problems.
* Strong leadership, communication, stakeholder-management, and prioritisation skills.
* Ability to operate effectively with internal teams and external technology partners.
