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This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform.
$182,400 - $247,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with finance and quantitative modeling; programming experience in any general-purpose language, either academic or professional, emphasizing code quality, clarity, style, and decomposition; experience with Apache Spark, Amazon Web Services ecosystem, including Lambda, EMR, EC2, Redshift, RDS, Athena, API Gateway, Cloudwatch, Step Function.
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Experience in BigData solutions like Apache Spark, Flink, Kafka, Hive, etc. Knowledge in CICD, Jenkins, Docker/Kubernetes, Elastic Search, Splunk/ELK, and Git; Used various data formats that include XML, JSON, and Parquet.
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3+ years of experience with big data frameworks (Amazon EMR, Apache Spark) Work on public cloud infrastructure, Big data technologies, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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4+ years of experience with container & image management (AWS EKS, Kubernetes, Docker) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) Utilize programming languages like Java, Python, SQL, Node, Go, and Scala.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). The tech stack is primarily AWS ECS with services written in Go, and DynamoDB as a back end datastore.
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Experience with Big Data platforms such as Apache Spark, EMR, EKS, Flink. Architect and implement ETL platforms with open-source technologies such as Spark on Kubernetes, EMR, S3 / SQS.
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Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
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Familiarity with Apache Hudi, Apache Beam, Apache Flink, Google Cloud Dataflow, Amazon Kinesis Data Analytics, and/or Azure Databricks. Experience with data integration tools like Apache Kafka, Flume, and NiFi.
$87,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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You Have: 8+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake or Databricks for Data Engineering or Machine Learning workloads. 5+ years orchestrating and implementing pipelines with workflow tools like Databricks Workflows, Apache Airflow, or Luigi 3+ years of experience prepping structured and unstructured data for data science models.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
$157,700 - $213,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Must have development experience on pyspark, apache spark technologies. Tech stack will require the use of Azure Databricks, pyspark, blob storage, azure monitor, application insights, azure key vault, docker containerization, Azure devops, bash script, powershell, data lake.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL Amazon Web Services (Security Groups, Batch, Lambda, SSH, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis.
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We are seeking a Senior Manager, Software Engineering, Back End who is passionate about marrying data with emerging technologies in Machine Learning and Generative AI space. 9+ years of experience in at least one of the following: Java, Scala, Python, or Go.
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New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Software Engineering. This role is for a Senior Manager position on Capital One’s Enterprise Feature Platform, focused on the retrieval and materialization of machine learning features.
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