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As an integral part of our team, you will not only need to tackle operational challenges at every layer of the system infrastructure, but also set up essential tools like Spark, Databricks, Snowflake, Kubernetes, and Kafka for data science infrastructure.
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Experience using big data technologies and distributed computing engines, e.g. HDFS, Spark, Kafka, Cassandra, Solr, Dask. Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform.
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Experience designing and implementing event driven systems leveraging message broker, event bus and streaming technologies like IBM Message Broker/MQ, IBM IIB, AWS Managed Kafka, Confluent connectors etc.
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At least 2 years of experience with distributed database systems (Cassandra, ElasticSearch, or Kafka) Strong understanding of distributed stateful applications (Cassandra, Elasticsearch, Kafka.
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Kubernetes, Helm, Terraform, Docker, Airflow, Grafana, Prometheus, Kafka, Kubernetes, Robots, Robotics, Boston Dynamics AI Institute, Machine Learning, ML, Artificial Intelligence, AI. Infrastructure Engineer, Senior Infrastructure Engineer.
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Develop and maintain interfaces with SOAP/XML and messaging software such as MQ Series, Tibco, MSMQ, Sonic MQ, and Open JMS. Familiarity with messaging software and protocols, including MQ Series, Tibco, MSMQ, Sonic MQ, and Open JMS.
ExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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AWS managed services: DynamoDB, S3, Postgres SQL, EKS, Amazon Kafka (MSK), OpenSearch etc. Minimum 8 years of hands-on experience with REST APIs including micro services architecture and other middleware, event driven development tools & components (MQ, KAFKA, SOA, ESB.
$138,870 - $169,730 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience with data warehouse and big data technologies such as Azure Synapse Analytics, Azure Data Lake Storage, Spark, Kafka, Databricks, and Containers. Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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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.
$97,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, HBase. Architect and develop large-scale, distributed data processing pipelines using technologies like Apache Spark, Apache Beam, and Apache Airflow for orchestration.
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5+ years of experience in wide variety of distributed systems and frameworks such as Apache Spark, Kafka, Airflow, TensorFlow , Docker, Snowflake and more. 5+ years of experience in wide variety of distributed systems and frameworks such as Apache Spark, Kafka, Airflow, TensorFlow , Docker, Snowflake and more.
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We are seeking a highly skilled and motivated Software Engineer II with experience in full-stack development, specifically with proficiency in TypeScript, React, CI/CD, Kafka, and application scaling.
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Experience with any of the following tools and technologies: Snowflake, Airflow, Python, AWS S3, AWS Lambda, AWS Batch, Terraform, Kafka, MySQL, Tableau, PagerDuty, DataDog, Jira, Confluence, Bitbucket, Alation.
$116,800 - $175,200 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Experience with orchestration tools such as Airflow, Dagster, or Prefect, with big data tools such as Kafka & Spark, and with dbt. Driving Results: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, SQL (using dbt for transformation), commercial SaaS and OSS offerings, and the entire AWS suite of technologies.
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Demonstrated Expertise (“DE”) designing and developing enterprise Web, multi-threaded, and concurrent asynchronous applications, and providing research and portfolio management capabilities on an investment decision support platform using Angular UI, Java Spring Boot microservices, messaging queues (TIBCO EMS and KAFKA), Oracle database, and Product Line/Structured Query Language (PL/SQL); and reviewing complex data comparisons using Integrity Check Engine for Data Quality ICEDQ tool.
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