Data Engineering Technical Lead, Samsung TV Plus

Position Summary

TV Plus Data Engineering Technical Lead

DESCRIPTION:

The Samsung global services team is responsible for driving Smart TV and mobile services businesses by building intelligent, integrated, cross-platform services that delight and entertain users.

Samsung TV Plus is Samsung’s direct-to-consumer OTT video service featuring ad-supported linear channels and ad-supported VOD. In the US, TV Plus launched in April 2018 and is currently available on 2016-25 model Samsung Smart TVs and recent Galaxy mobile devices.

As a data engineer, you will design, build, and maintain the infrastructure and systems that collect, process, and store large-scale data related to content, users, and advertising. The role is crucial for enabling data-driven decisions that shape product development, content strategy, and user experience.

Role and Responsibilities

KEY RESPONSIBILITIES

• Create blueprints for data systems, including data models, schemas, and workflows, that serve as a roadmap for data engineers
• Define and enforce data standards, policies, and best practices for data accuracy, integrity, and security across the organization.
• Oversee the architecture, security, governance, and optimization of the data lake, ensuring data quality, accessibility, and compliance.
• Develop and manage data pipelines that leverage APIs to extract, transform, and load data from internal and external sources into the data lake.
• Continually evaluate effectiveness of existing workflows, systems, and integration points versus latest technologies
• Bridge the gap between business stakeholders and data teams by translating complex business requirements into scalable technical data solutions.
• Design and implement robust data integration and transformation processes to ensure seamless, governed large volumes of data flows across operational and analytical systems, ensuring data availability and reliability.
• Evaluate and recommend appropriate technologies, platforms, and tools, including cloud services (mainly AWS), big data platforms (Hadoop, Spark), and databases.
• Drive data quality initiatives by identifying systemic issues and implementing proactive solutions to improve data reliability and usability.
• Automate the deployment and management of data pipelines and related resources using Terraform, ensuring efficient and consistent deployments across environments

Skills and Qualifications

QUALIFICATIONS

• Bachelor's Degree required. Degree in Engineering or Computer Science preferred
• 10+ years of experience in roles like data engineering, data architecture which support a large-scale data and services
• Expertise in major cloud platforms such as AWS, Azure, and Google Cloud, along with experience in large-scale data solutions
• Deep understanding of data warehousing, ETL/ELT processes, SQL, and PySpark, Python, AWS services like Glue, Athena, Lambda, S3
• Strong understanding and practical experience with data modeling, creating, and managing comprehensive data infrastructure.
• Experience establishing and enforcing frameworks for data governance, compliance, security, and quality standards across enterprise systems.
• Optional qualifications include experience with building data pipelines for ML models, familiarity with ML frameworks like TensorFlow or PyTorch, and knowledge of MLOps practices.
• Experience in writing, maintaining, and troubleshooting Terraform configurations and modules for cloud platforms
• Experience collaborating with a globally distributed team

Compensation for this role, for candidates based in Mountain View, CA is expected to be between $195,000 ~ $240,000 or based in Los Angeles, CA is expected to be between $180,000 ~ $220,000.  Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role. 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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