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Familiarity with Snowflake, Monte Carlo, RDS, DynamoDB, Kafka, Fivetran, dbt, Airflow, Docker, Kubernetes, EMR, Sagemaker, DataDog, PagerDuty, Atlan, Data Observability tools and Data Governance tools.
$235,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Extensive experience with Kafka, Spark, Redis, Flink, Trino/Presto, Hadoop in complex on-premise and hybrid data environments. Technical Leadership: Leverage your deep expertise in data technologies such as Kafka, Spark, Redis, Flink, Trino/Presto, and Hadoop to lead the architecture and development of our data systems, ensuring optimal performance, reliability, and scalability.
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Backend: Ruby on Rails, GraphQL, Kafka. Key Focus Areas: Monetization Optimization : Architect and refine backend systems that support dynamic pricing models and feature gating. We are looking for a seasoned Senior Backend Engineer to help architect and implement backend systems that are critical to our monetization and retention strategies.
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Experience working with: Hadoop, Spark, Kafka, Scala, Python, R etc. Architect, build, maintain, and improve end to end ML systems. Experience with CNN training and deep learning frameworks such as PyTorch, Tensorflow, Keras or similar.
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Open Source Frameworks - Spring boot, Spring CoreMessaging frameworks such as Kafka, Tibco EMS or JMSOracle PL/SQL JavaScript and scripting frameworks (JQuery, AngularJS)Hands-on experience in test automation at various levels of testing (unit, component, integration and functional tests.
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Technical Proficiency: Expertise in web and data technologies such as Kafka, HDFS, Spark, EMR, Open Table Formats, Snowflake, Hive, HBase, Scylla, Django, and FastAPI. The Principal Architect will lead the development and maintenance of the architectural vision for the company's software systems, providing technical oversight and strategic insight into their evolution.
$350,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hadoop, S3, AWS, Google Cloud etc. We are also the engine that drives a fully functional world class data warehouse on top of Hadoop, this means providing tools to define data cubes and syncing high load of data from a processing Hadoop to other systems using in-house built Applications.
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Knowledge of distributed computing technologies such as Apache Spark, Hadoop, or Dask, and experience with containerization and orchestration technologies such as Docker and Kubernetes. Requirements Key Responsibilities: Machine Learning Infrastructure Design: Design and architect scalable and reliable infrastructure solutions to support machine learning model development, training, and deployment.
$230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Required : Overall 10+ years of experience in Technology with 3+ years of experience in Microservices (Java / Spring Boot), any NoSQL DB (Mongo, Cassandra, or equivalent), RDBMS (Oracle, MySQL or equivalent), Cloud (Azure, Google Cloud Platform or AWS), 1+ year(s) of experience in Kafka event processing, 2+ years of experience in Front End like ReactJS, Angular or equivalent, 1+ year of experience in iOS / Android app development.
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Preferred qualificationsHave experience in Java, Scala (Spark), or RubyExperiences with big-data technologies such as Spark, Presto, Kafka, and Flink, and OLAP preferredNote that It’s not expected that any single candidate would have expertise across all of these areas.
$269,200Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with Kafka and streaming data processing. Hands-on experience with Kafka, Flink, Spark, or Pulsar. Kafka is a big part of how our systems communicate. Architect, design, and implement a scalable and highly available Streaming Ingest Platform based on Kubernetes, mostly Java with some java script, Go, Rust, React, PostgreSQL and Redis.
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Design, develop, and own robust, scalable data processing and data integration pipelines using Python, dbt, Kafka, Airflow, PySpark, SparkSQL, and REST API endpoints to ingest data from various external data sources to Data Lake. Develop testing frameworks and monitoring to improve data quality, observability, pipeline reliability, and performance Orchestrate sophisticated data flow patterns across a variety of disparate tooling.
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Must have: Strong knowledge of Spark, Hadoop, or Cloudera. Knowledge of one of the major business intelligence vendors, such as Tableau, Power BI, Quick Sight, Qlik, Sisense, Domo, or Looker. Must have: Strong knowledge of Spark, Hadoop, or Cloudera.
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Familiarity with big data technologies (batch or streaming) such as BigQuery, Spark, Athena, Kinesis, Kafka, PubSub, etc. Familiarity with big data technologies (batch or streaming) such as BigQuery, Spark, Athena, Kinesis, Kafka, PubSub, etc.
$247,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Mastery in Python, Java and SQL for complex operations within Snowflake, and AWS services like DMS, MSK (Kafka) and S3. Foster and facilitate internal technical sessions, exploring nuances of AWS data services like DMS, MSK (Kafka) , and S3, and sharing best practices for integration with the broader data stack.
$264,000 a yearFull-timeExpandApply NowActive JobUpdated Today
hadoop kafka jobs Title: architect in San Francisco, CA
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