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A discernible passion for data engineering: especially around large-scale data processing. Our data is stored in S3, RDS MySQL, Redis, ElasticSearch, and Aurora. Our services are deployed to Kubernetes using Docker, and use Kafka for stream-processing.
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Preferred experience in one or more of the following areas: Message Queuing Services (Kafka, Amazon Simple Queue Service), Data Processing Frameworks (Apache Spark, Apache Flink), Key Value Stores (Redis, DynamoDB, Memcached, Riak), Document based DBs (MongoDB, Cassandra), Container Orchestration (Kubernetes, Mesos), ML Ops.
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Experience designing and building highly available, distributed systems of data extraction, ingestion, normalization and processing of large data sets in real time as well as batch, that will be used across engineering teams using orchestration frameworks like Airflow, KubeFlow or other pipeline tools.
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Have 7+ years of experience in web application development or software engineering in a large enterprise environment using Java, including familiarity with modern frameworks and platforms (e.g., Spring, Docker, Kubernetes, Kafka.
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By integrating experience design, complex engineering, and data expertise—we help our clients imagine what’s possible, and accelerate their transition into tomorrow’s digital businesses.
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As an engineering team, we are working on improving our systems to use the latest technologies (Spring Boot, Java 17, Kafka, etc.) We use PostgreSQL for our databases, and Python & Spark for large scale data workloads.
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We’re using React, TypeScript, Tailwind CSS, Python, PostgreSQL, and Kafka. You’ll also lay the groundwork for engineering and product processes, ensuring that our team can continue to build quickly and serve our customers for years to come.
$142,500 - $231,000 a yearFull-timeExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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Experience with big data tools: Hadoop, Spark, Kafka, Spark & Kafka Streaming, Python, Scala, and Talend Advanced working SQL experience working with relational databases, query authoring (SQL) and working familiarity with a variety of databases.
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You've worked with data processing tools such as Kafka, Spark, Flink, data lakes, etc. About Satsuma Reliable blockchain indexing & querying for web3 engineering teams. Build and scale our infra for ingesting, transforming, and exposing blockchain data in real-time.
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Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc. In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers.
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5+ years of experience in data engineering or a related field required. Knowledge of one or multiple of the tools: Hadoop, Spark, Presto, Hive, Kafka, or Airflow. Create the pipeline for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources.
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You will be collaborating closely with the human / animal brain data acquisition and AI engineering teams, building the interface between data-acquisition and our machine learning models.
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As an Expert Java Streaming Technical Lead at PG&E, you will play a pivotal role in providing technical leadership and mentorship within our Flink and Kafka real-time data platform and product engineering teams.
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Have experience with relational or NoSQL databases in production (we use MySQL, Redis, and Cassandra)Have experience with open-source distributed systems technologies (we use Kafka, Finagle, Kubernetes, and Docker.
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We use open source technologies like ClickHouse, Kafka, and Kubernetes to help us deliver on our mandate, and we use our expertise to build opinionated data engineering solutions appropriate for the challenges Sentry faces as an observability company.
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data engineering kafka jobs in San Francisco, CA
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