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Summary:
You will be involved in solving problems related to data processing and preparation for use in advertising recommendation systems. This position combines data engineering and back-end programming skills. The ability to interact with different teams and discover their data problems and requirements is one of the most important tasks of this responsibility. Optimization of advertising recommendation systems in the web space is another important task of this position.
Responsibilities:
- Designing, building, and maintaining scalable and efficient data pipelines for processing and storing large-scale datasets.
- Integrating and transforming data from various sources to support analytics, machine learning, and business applications.
- Developing and optimizing APIs for seamless interaction between data systems and applications.
- Ensuring data quality, integrity, and availability through robust data infrastructure and monitoring systems.
- Collaborating with data scientists and analysts to provide clean, accessible, and well-structured data for advanced analytics and modeling.
- Implementing and maintaining data storage solutions, including relational and non-relational databases, to support business needs.
- Continuously improving data workflows and infrastructure for performance, scalability, and reliability.
Requirements:
- Strong problem-solving skills and a methodical approach to building data systems.
- Proficiency in Python and relevant data engineering libraries/tools such as Pandas, NumPy, and SQLAlchemy.
- Expertise in designing and implementing data pipelines using orchestration tools like Apache Airflow, Prefect, or similar.
- Experience with relational databases (e.g., PostgreSQL, MySQL) and non-relational databases (e.g., StarRocks, Elasticsearch).
- Strong knowledge of database internals, including indexing, query optimization, and performance tuning.
- In-depth understanding of operating system concepts, such as memory management, process scheduling, and file systems.
- Familiarity with big data technologies such as Apache Spark, Hadoop, or Kafka for processing large-scale datasets.
- Enthusiasm for optimizing data infrastructure and staying updated with emerging data engineering tools and practices.
- Familiarity with software architecture concepts and API design.
- Experience in using Docker and Kubernetes to manage execution environments
- Enthusiasm for learning and analyzing issues related to digital marketing
Effective communication skills:
- Regularly achieve consensus with peers, and clear status updates.
- Comfort working in a highly agile, intensely iterative software development process.
- open to learning about new technologies and sharing your knowledge with others.
- Self-motivated and self-managing, with great organizational skills.
- Domain knowledge relevant to the product stage in which you are looking to join.