Sr. Data Engineer
Indexed description
The Samsung TV Plus is seeking a Senior Data Engineer to join our Data Analytics & Insights team to architect, scale, and optimize our global data platform. You will own high-performance data infrastructure, design robust ETL/ELT pipelines, and manage our cloud data warehouse environment — directly enabling advanced analytics, ROI measurement, and AI deployment across global engineering and analytics teams.
Role And Responsibilities
Key Responsibilities
- Data Platform & Warehouse Architecture: Own the technical design, implementation, and scaling of our enterprise cloud data warehouses and centralized cloud storage platforms. Lead performance tuning, cost optimization, and query scaling strategies.
- Pipeline Development (ETL/ELT): Build, monitor, and maintain robust batch and streaming data pipelines using SQL, Python, and modern workflow orchestration engines to ingest high-volume, global streaming datasets.
- Modern Data Modeling: Architect clean, modular, and optimized analytics schemas using automated data modeling and transformation frameworks to ensure reliable, analysis-ready datasets.
- Data Observability & Governance: Establish rigorous data quality frameworks, observability metrics, and automated monitoring tests to ensure end-to-end pipeline reliability and prevent data downtime.
- Global Stakeholder Collaboration: Partner with cross-functional engineering, analytics, and business stakeholders in LA and Korea HQ to translate complex business logic into scalable data schemas and robust systems.
- Technical Leadership: Mentor junior engineers, establish best practices for data engineering (CI/CD, code reviews, version control), and champion modern data stack methodologies across the organization.
- Education: Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related quantitative discipline (Master's preferred).
- Experience: 8+ years of professional experience in data engineering, backend software engineering, or data platform architecture.
- Core Technologies (or equivalent tools):
- Cloud Data Warehousing: Extensive hands-on experience designing and managing enterprise environments in Snowflake (or Databricks, BigQuery, or equivalent cloud data warehouses).
- Languages: Advanced proficiency in Python and SQL (analytical functions, window functions, and query optimization).
- Data Transformation: Production experience with dbt (or equivalent SQL-based transformation frameworks).
- Pipeline Orchestration: Experience orchestrating complex pipelines using Apache Airflow (or Prefect, Dagster, or equivalent workflow orchestrators).
- Cloud Infrastructure: Practical experience with the AWS ecosystem (or GCP, or equivalent cloud platforms).
- Infrastructure & CI/CD: Familiarity with Infrastructure as Code (IaC) tools like Terraform (or CloudFormation, Pulumi, or equivalent tools) and CI/CD version control workflows.
- Data Modeling: Deep understanding of data warehousing methodologies and Star schema design.
- Data Observability & Governance: Using tools like Snowflake DMFs, Great Expectations, Monte Carlo, or dbt test to ensure end-to-end pipeline reliability.
- BI Integration: Functional understanding of BI server modeling layer integrations (e.g., PowerBI, Tableau, or equivalent).
- Media & AdTech Context: Experience working with digital media, streaming analytics, or AdTech datasets.
- Cross-cultural Collaboration: Experience working with global teams across different time zones (specifically collaborating with Korea tech HQ).
Regular full-time employees (salaried or hourly) have access to benefits including: Medical, Dental, Vision, Life Insurance, 401(k), Employee Purchase Program, Tuition Assistance (after 6 months), Paid Time Off, Student Loan Program (after 6 months), Wellness Incentives, and many more.
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