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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Warehouse Engineering Manager - **Company:** Samsung - **Location:** Los Angeles, CA, United States - **Experience:** Expert - **Salary:** $180,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Big Data, Cloud Storage, Data Visualization, Data Warehousing, Decision Support Systems, Power BI, DataOps, SQL Databases, Data Streaming, Tableau (Software), Cloud Platform System, Information Technology, Data Analytics, Performance Monitor, Looker Analytics, Data Pipelines - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=bab633e360e21bdd ## About the Role * Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, or a related quantitative discipline. * 8+ years of experience in data operations, analytics engineering, or a closely related analytics support role. * Strong proficiency in SQL and experience working with large, complex datasets. * Hands-on experience integrating internal and third-party data sources into cloud-based data platforms (AWS preferred). * Demonstrated ability to identify, troubleshoot, and resolve data quality and pipeline issues. * Strong analytical rigor, attention to detail, and comfort operating in a fast-paced, cross-functional environment. Preferred Qualifications: * Experience working with BI and visualization tools (e.g., Tableau, Power BI, Looker). * Familiarity with data orchestration and transformation tools (e.g., Airflow, dbt, or similar). * Exposure to ROI modeling, KPI frameworks, or asset-level performance analytics. * Strong written and verbal communication skills, with the ability to support executive-level analysis and storytelling. ## Description The Samsung TV Plus group is seeking a Data Warehouse Engineer to support the build-out and scale of our Global Data Analytics & Insights (DAI) practice. This role is critical to ensuring that high-quality, trusted, and timely data flows from internal and third-party sources into our analytics ecosystem, enabling advanced analysis, ROI measurement, and asset-level performance reporting. You will partner closely with Analytics, Engineering, and Business stakeholders from Korea headquarters as well as regional offices to operationalize global data pipelines, ensure data accuracy and availability, and troubleshoot complex data quality issues. This role is foundational to enabling data-backed strategic decision-making and content investments, and the adoption of advanced AI-driven analytics capabilities., * Own the ingestion and operationalization of internal and third-party data sources into centralized cloud storage (AWS S3) to enable enterprise analytics and insights. * Ensure the accuracy, timeliness, and reliability of data pipelines supporting ROI analysis, asset-level dashboards, KPI monitoring, and executive decision support. * Partner closely with the Engineering and Analytics teams across the globe to troubleshoot data quality issues and translate business requirements into scalable data solutions. * Enable high-stakes business insights and narrative-driven analyses by providing trusted, well-governed, and analysis-ready datasets. * Support the adoption of advanced analytics and AI capabilities by ensuring robust data foundations and operational excellence. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)