Data Architect
September 20
Description
• Design and implement scalable, robust, and secure data architectures that support data analytics, machine learning, and business intelligence needs across the organization. • Create and optimize data models (e.g., star schema, snowflake schema) to ensure data is structured for efficient access and analysis. • Lead the architecture of data warehouses, data lakes, and data pipelines, utilizing cloud platforms like AWS (e.g., Redshift, S3, Glue, Lambda). • Ensure that data governance, privacy, and security best practices are followed throughout the data infrastructure. • Collaborate with data scientists, data engineers, and BI teams to design solutions that support video streaming optimization, personalized content recommendations, and location-based analysis. • Develop strategies to manage and process large datasets, including real-time streaming data from user activity, video content performance, and other key metrics. • Evaluate and implement emerging technologies related to data storage, ETL processes, and cloud computing to continuously improve data architecture. • Create and maintain comprehensive documentation of data systems, processes, and architecture. • Mentor and guide other members of the data engineering and architecture team, ensuring that best practices and standards are adhered to.
Requirements
• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field. • 7+ years of experience in data architecture, data engineering, or related fields. • Proven experience in designing and implementing data architectures for large-scale, data-intensive applications, preferably within the video streaming or entertainment industry. • Strong proficiency with cloud platforms, particularly AWS (e.g., Redshift, Glue, Lambda, S3, Kinesis). • Deep understanding of database management systems (e.g., PostgreSQL, MySQL, NoSQL databases) and data modeling techniques (e.g., star schema, snowflake schema). • Experience with big data technologies such as Hadoop, Spark, Kafka, and other streaming data frameworks. • Expertise in building and managing ETL/ELT pipelines, data lakes, and real-time data streaming architectures. • Familiarity with data governance, data security, and compliance standards such as GDPR. • Strong problem-solving and analytical skills with a focus on creating efficient and scalable solutions. • Excellent communication skills, with the ability to convey technical information to non-technical stakeholders.
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