Lead/Senior Data Engineer
We are looking for a skilled and driven Data Engineer to join the oneD team. You will design, build, and maintain scalable data pipelines and infrastructure that support the end-to-end data lifecycle across AVOD, SVOD, personalization, customer journeys, and core platform services.
Your primary focus will be engineering reliable data systems—but you’ll also play a key role in enabling product analytics, subscription insights, experimentation, CRM, recommendation engines, and business-critical reporting by collaborating closely with product, engineering, analytics, and operations teams.
Key Responsibilities
✅ Core Data Engineering
- Design, build, and maintain scalable ETL/ELT pipelines using AWS services and modern data engineering tools.
- Develop and optimize data workflows across backend services, product analytics, marketing platforms, subscription systems, and third-party integrations.
- Build and manage data infrastructure using services such as S3, Redshift, Athena, Glue, Lambda, MWAA, or similar technologies.
- Improve data freshness, reliability, observability, performance, and cost efficiency across the data platform.
- Support migration and modernization of legacy data workflows into scalable and maintainable architectures.
⚙️ Core Application Data
- Ingest and consolidate data from core platform services including user authentication, session logs, content metadata, APIs, and platform events.
- Support event tracking and instrumentation across playback, search, discovery, subscription journeys, engagement funnels, and user behavior.
- Partner with product and engineering teams to ensure reliable data collection and event quality.
- Prepare trusted raw and staging datasets for analytics, experimentation, CRM, personalization, and recommendation use cases.
📺 AVOD & Monetization Data
- Build and maintain pipelines for ad requests, impressions, clicks, revenue, and audience data from advertising and monetization platforms.
- Support AVOD reporting, yield optimization, audience segmentation, and advertising performance analysis.
- Enable reliable measurement of fill rate, CPM, engagement, and monetization KPIs.
💳 SVOD & Subscription Data
- Build and maintain datasets supporting subscription lifecycle analytics, including acquisition, conversion, renewal, retention, churn, and reactivation.
- Integrate data from subscription systems, payment platforms, CRM systems, and partner channels.
- Support experimentation frameworks and personalization initiatives through reliable data infrastructure.
🔒 Data Quality, Governance & Security
- Build monitoring, alerting, and validation processes to ensure trusted and reliable datasets.
- Establish data quality standards, lineage tracking, and anomaly detection processes.
- Support governance, security, and compliance requirements in accordance with company policies and PDPA requirements.
🤝 Cross-Team Collaboration
- Collaborate with Product, Engineering, Analytics, Marketing, and Business teams to understand and deliver data requirements.
- Troubleshoot data issues across multiple systems and improve stakeholder confidence in data.
- Contribute to data engineering standards, documentation, and best practices.
Qualifications
Must-Have
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
- 3+ years of experience in Data Engineering or related roles.
- Strong SQL and Python skills.
- Hands-on experience with cloud-based data platforms, preferably AWS.
- Experience with Redshift, BigQuery, Snowflake, Databricks, or similar data warehouses.
- Experience with orchestration tools such as Airflow, MWAA, Dagster, Prefect, or similar.
- Strong understanding of data pipelines, data quality, and production data workflows.
- Strong problem-solving and communication skills.
- Thai nationality only.
Nice-to-Have
- Experience with AWS services including S3, Athena, Glue, Lambda, Redshift, MWAA, IAM, or related services.
- Experience with OTT, streaming, media, subscription, gaming, e-commerce, or consumer platforms.
- Experience with event tracking, behavioral analytics, experimentation, or recommendation systems.
- Familiarity with Git, CI/CD, monitoring, testing, and data observability practices.
- Experience with dbt or modern data stack technologies.








