Descrizione
Job Description The lead data engineer is a senior software developer with strong software engineering skills who is responsible for building custom open-source-based data ingestion and MLOps platforms. He/she has deep appreciation of the complexity of the data engineering process, such as the challenges of data ingestion involving large or near-real-time datasets, the maintenance of high data quality, and the importance of automation for increasing pipeline robustness and reducing the need for human intervention.
Responsibilities
• Be an effective distributed-system implementer in the following core activities: o Design and develop data engineering services and their ecosystem using distributed databases (relational, columnar, graph, in-memory); orchestration (Apache Airflow); and distributed stream/batch data processing (Kafka, Kinesis, Spark). o Design and develop MLOps production pipelines; provide technical support to data scientists/ML engineers by getting their ML/DL models deployed at scale and meeting SLAs on both cloud and on-premises GPU and CPU instances. o Design data models for mission-critical, high-volume, near-real-time/batchdata; build idempotent/atomic production data pipelines to make data ingestion more fault tolerant.
o Design and develop intuitive, highly automated, self-service data platform functions for business users. o Design, build, and operate scalable and reliable data pipelines on the Databricks platform. • Explore, evaluate and champion the in
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