The role involves creating data pipelines to ingest, cleanse, and standardize data based on input from data scientists and data modelers. Once data is processed, the individual applies machine learning algorithms to ensure production performance readiness. The position requires activating models through microservices, reporting, dashboards, or emails. The work includes managing data structures, algorithms, and distributed storage and compute systems.

The role requires a minimum of three years of experience in building data pipelines using big data or cloud technologies. Candidates must possess hands-on experience with the Hadoop ecosystem, including HDFS, MapReduce, Hive, Pig, Impala, Spark, Kafka, Kudu, and Solr. Proficiency in DevOps practices, such as source control and continuous integration, is required. Additionally, the position necessitates experience with containerization technologies like Docker and Kubernetes.