Analytics Engineer & Data Modeling

About the Role

We are looking for a skilled and driven Analytics Engineer to join the oneD team. You will build trusted data models, metric frameworks, and business-ready datasets that power decision-making across AVOD, SVOD, personalization, product development, marketing, content, and core platform services.

Your primary focus will be transforming raw data into reliable, reusable, and well-documented analytical assets—but you'll also play a key role in enabling subscription growth, advertising optimization, experimentation, customer engagement, and executive reporting by collaborating closely with product, engineering, business, and leadership teams.

Key Responsibilities

📊 Business Data Modeling & Analytics

• Design and maintain trusted business data models covering users, subscriptions, content, viewing behavior, engagement, revenue, campaigns, and product events.
• Build source-of-truth datasets and analytical data marts that support reporting, experimentation, CRM, personalization, and business intelligence.
• Define, document, and maintain business metrics including Active Users, Paid Subscribers, Churn, Retention, Renewal, Reactivation, Conversion, Watch Starts, Revenue, ARPU, and LTV.
• Establish consistent business logic and metric definitions across reporting and analytics platforms.

📺 AVOD & Monetization Analytics

• Build analytical datasets supporting advertising performance, inventory optimization, audience segmentation, monetization, and revenue reporting.
• Develop trusted business models for impressions, clicks, fill rate, CPM, yield, and content monetization.
• Support data-driven decisions across advertising and monetization initiatives.

💳 SVOD & Subscription Analytics

• Develop analytical models covering subscription acquisition, conversion, renewal, churn, retention, and customer value.
• Enable subscription funnel analysis, cohort analysis, pricing evaluation, campaign effectiveness, and partner performance measurement.
• Support product growth initiatives through trusted subscription and engagement datasets.

🎬 Product & Content Analytics

• Create business-ready datasets supporting playback analytics, content performance, search, discovery, recommendation, and engagement analysis.
• Support experimentation, A/B testing, customer journey optimization, and personalization initiatives.
• Build reusable analytical datasets that enable Product, Marketing, Content, and Business teams to self-serve insights.

📈 Data Quality, Documentation & Governance

• Improve data testing, documentation, lineage, and reliability of analytical models.
• Reduce duplicated business logic across reports, dashboards, and ad-hoc analysis.
• Partner with Data Engineers to improve upstream data quality and source data consistency.

🤝 Cross-Team Collaboration

• Work closely with Product, Marketing, Content, Finance, Operations, and Leadership teams to translate business requirements into scalable data models.
• Act as the owner of business-facing metric definitions and trusted datasets.
• Enable stakeholders to make faster and more confident decisions through reliable data assets.

Qualifications

Must-Have

• Bachelor's degree in Computer Science, Engineering, Information Systems, Statistics, or related field.
• 3+ years of experience in Analytics Engineering, Data Modeling, BI Engineering, Data Warehousing, or related roles.
• Strong SQL skills and experience building business-facing datasets.
• Experience with dbt or similar transformation frameworks.
• Experience with Redshift, BigQuery, Snowflake, Databricks, or similar analytical warehouses.
• Strong understanding of data modeling, metric design, dimensional modeling, and analytical data architecture.
• Strong documentation habits and attention to data quality.
• Ability to communicate effectively with both technical and business stakeholders.
• Thai nationality only.

Nice-to-Have

• Experience with AWS analytics stack including Redshift, Athena, Glue, and S3.
• Experience with OTT, streaming, media, subscription, gaming, e-commerce, or consumer platforms.
• Experience with CRM, experimentation, personalization, recommendation systems, or customer behavior analytics.
• Familiarity with BI tools such as Tableau, Power BI, Looker, QuickSight, Metabase, or similar.
• Python experience for automation, validation, or exploratory analysis.
• Experience supporting executive reporting and business performance management.