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We use Apache Airflow, Python, and Apache Spark for ETL. For streaming data, we use Apache Kafka managed by a vendor and use Kafka Connect, Kafka Streams, and Spark Streaming for stream processing.
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Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt. Modern ETL tools (Apache Beam, Kafka, Spark or similar) Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt.
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Design efficient data synchronization processes between on-premises Oracle databases and Snowflake using Kafka and CDC extraction tools. Data Integration: Experience with Kafka and CDC tools (like Debezium connector) for real-time data synchronization.
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Experience with high-speed distributed computing frameworks Apache Flink, AWS EMR, Hadoop, HDFS, MapReduce, Apache Spark, Kafka Streams. Java (8/11/17), Cloud (AWS), Apache Flink, Kafka, Jenkins, Harness, Maven/Gradle.
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Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake) Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink.
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1 year of experience with technologies such as Kafka, RabbitMQ, SQS, Ansible, Terraform, Docker and Kubernetes, Jenkins, Spinnaker, Azure DevOps, TeamCity. 1 year of experience with technologies such as Kafka, RabbitMQ, SQS, Ansible, Terraform, Docker and Kubernetes, Jenkins, Spinnaker, Azure DevOps, TeamCity.
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Strong understanding of the following verticals: IT Operations, DevOps, Site Reliability Engineering, Application Monitoring, Enterprise Integration, Enterprise Service Bus, Event Based Architecture, Kafka.
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Proven exposure to distributed messaging / streaming platforms (Apache Kafka) Experience with one or more of the following technologies: Front-end development frameworks (Angular, React or Vue.js), Cloud services (Microsoft Azure), Message queue-based designs/implementations, Git code repositories, Reporting services (Power BI, Kibana), FIX protocol.
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Experience with building stream-processing systems, using solutions such as Kafka, Storm or Spark-Streaming. Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark.
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At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing and blockchain. Prior experience with AppDynamics, Dynatrace, MoogSoft, Splunk, Datadog, ServiceNow, MuleSoft, Tibco, Software AG, etc.
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Utilize technologies like ReactJS, Node JS, PostgreSQL, GCP, Pivotal Cloud Foundry, SpringBoot, GraphQL, Coveo Search Engine, HCL Commerce, Apache Kafka, APIGEE, JAVA, Adobe Experience Manager, Event-Driven Architecture, Reactive Architecture, and SAP integrations.
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At least 2 years experience with coding and scripting (Python, SQL, Java, JavaScript, Golang, Bash, Perl or Ruby) At least 2 years of experience with distributed database systems (Cassandra, ElasticSearch, or Kafka.
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Queer-Inclusive Benefits: Industry-leading gender-affirming offerings with up to 90% cost coverage, access to Included Health, monthly stipends for HRT, and more. We work with companies funded by the best investors including Sequoia Capital, Lightspeed Ventures, Tiger Global Management, A16Z, Accel, DFJ, and more.
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Cloud Platforms: Knowledge of cloud infrastructure and services, preferably Azure, as it relates to Snowflake and Databricks integration. Utilize Snowflake and Databricks for advanced reporting and analytics, providing actionable business insights.
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Hands-on experience with Kafka, Flink, Spark, or PulsarExperience designing systems that integrate 3rd party code and componentsExperience with Kafka and streaming data processingFostering a diverse, welcoming and inclusive environment is important to us.
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