business objectives. Assess and choose appropriate data storage solutions, including relational databases, data manipulation. Experience with both SQL and NoSQL data storage. Familiarity with data processing frameworks
mmend techniques and strategies to optimize data storage, reporting, and analysis
sources into a data warehouse or other storage systems Creating and optimizing data storage solutions for
reporting models and solutions • Maintaining data storage, assess database design and gather, organize
tuning and optimization of data pipelines and data storage solutions to ensure optimal performance and and data querying. Experience with cloud-based data storage solutions such as AWS S3 or Azure Blob Storage
systems. Implement best practices for big data processing, storage, and analysis. Develop and maintain documentation preferably Azure. Strong knowledge of big data processing, storage, and analysis technologies (Hadoop, Spark
cleaning techniques. Build and manage scalable data storage and processing systems using distributed frameworks PySpark, Scala Big Data Processing Frameworks: Apache Hadoop, Spark, Flink Distributed Storage: HDFS, Cloud
infrastructure and systems that enable efficient data processing, storage, and retrieval. You will also help ensure and optimize data models to ensure efficient data storage, retrieval, and analysis. Develop and maintain
sequence formats (FASTQ etc.). Understanding of data storage (S3-Buckets). Experience with validation and
data clients to consume RESTful APIs Integrate data storage solutions, including databases, key-value stores