Data Engineer
Found in: beBee jobs US - 2 weeks ago
Prior experience must include:
Design a cloud-based streaming analytics service for high scalability and fault tolerance, utilizing fully managed services (like GCP Cloud Dataflow, AWS Kinesis, Apache Kafka, and AWS EMR) and develop the data pipeline using unified engines (like Apache Beam and Apache Spark) for large-scale data analytics, leading development effort, guide QA and product teams to adhere to the required standards; Implement microservices, build a data ingestion API that was deployed on a serverless computing service (like AWS Lambda, Google Cloud Functions etc.) and collaborate with cross-functional teams to ensure the API meets business requirements and integrates seamlessly with other systems; Design and develop an ETL service using both functional programming languages (such as Clojure, Scala, etc.) and object-oriented programming languages (like Python, Java, etc.) and deploy service on managed container platform (e.g., AWS ECS, Google Kubernetes Engine) to ETL data from relational databases to distributed data warehouse (e.g., AWS Redshift, GCP BigQuery, Snowflake) and provision the resources with Infrastructure as Code tools (e.g., Ansible, Terraform); Develop data archival strategy for migrating data from search/analytics service (e.g., Elasticsearch, Apache Solr) to cost-effective object store (e.g., AWS S3, GCP Cloud Storage) with lifecycle policies for data retention and work with Project Manager to transform the solution into comprehensive project plan, including scope, estimations, deadlines, change management, and project management oversight.
100% remote work allowed from anywhere in the U.S. Please submit resume to , reference job #PERM-CA
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Found in: beBee jobs US - 2 weeks ago
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