Building data pipelines to ingest data from various sources such as databases, APIs, or streaming platforms. Integrating and transforming data to ensure its compatibility with the target data model or format.
Designing and optimizing data storage architectures, including data lakes, data warehouses, or distributed file systems. Implementing techniques like partitioning, compression, or indexing to optimize data storage and retrieval. Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency.
Designing and implementing data models that support efficient data storage, retrieval, and analysis. Collaborating with data scientists and analysts to understand their requirements and provide them with well-structured and optimized data for analysis and modeling purposes.
Collaborating with cross-functional teams including data scientists, analy...