Development of a Real-Time Data Pipeline for Genomic Research Analysis

As a growing player in the medical research field, we are faced with the challenge of managing and analyzing a rapidly increasing volume of genomic data. To maintain our competitive edge and expedite groundbreaking research, we require a robust real-time data pipeline. The project will involve designing a system that efficiently processes incoming datasets using Apache Kafka and Apache Spark, integrates data management practices via Airflow and dbt, and stores results in a scalable data warehouse like Snowflake or BigQuery. The solution should implement data observability features to monitor data quality and system performance continuously. Event streaming will also be employed to support real-time analytics, providing researchers with immediate insights. Collaborating with our data science team, the freelancer will ensure the pipeline is optimized for MLOps, facilitating seamless integration with machine learning models. This initiative is crucial in transforming our data operations, enabling faster hypothesis testing and validation.