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Expert knowledge of Apache Beam, Apache Spark, Kafka, Apache Flink, and Apache Pinot. The ideal candidate should have a strong background in a variety of data frameworks and tools, including but not limited to Apache Beam, Apache Spark, Kafka, Apache Flink, and Apache Pinot.
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Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements. Strong experience with Databricks and Apache Spark for data processing and analytics.
Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Design, develop, and maintain data pipelines using GCP services like Dataflow, Dataproc, and Pub/Sub, in addition to developing and implementing data ingestion and transformation processes using tools like Apache Beam and Apache Spark.
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Experience in Apache Spark, Databricks or similar distributed processing systems. Implement data pipelines using Apache Spark/Databricks. You will primarily be working on Apache Spark/DataLake/Airflow (in Python) and other cloud-based technologies.
Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Big Data Technologies - Apache Spark, Apache Kafka, Apache Flink. Minimum of 4+ years of experience in data engineering, focusing on DataBricks and/or Snowflake. Technical Expertise: Utilize expertise in DataBricks and Snowflake to design and implement scalable, reliable, and efficient data solutions.
ExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Extensive experience with Apache Spark and Databricks (or similar data processing frameworks). Design, develop, and implement efficient and scalable data pipelines using Apache Spark on Databricks.
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Data Processing: Develop and implement data processing pipelines using Apache Beam, Apache Spark, or other suitable frameworks to transform and cleanse data for analysis. Automation and DevOps: Implement automation scripts and workflows using tools like Terraform, Deployment Manager, or Google Cloud Deployment Manager to automate provisioning and management of GCP resources.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL. Utilize programming languages like Python and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
InternExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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2+ years of experience with Spark. Amazon Web Services (Security Groups, Batch, Lambda, SSH, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis) 2+ years of experience with Presto or Snowflake.
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Hands-on experience with big data technologies such as Apache Spark, Hadoop, and/or Databricks. Hands-on experience with big data technologies such as Apache Spark, Hadoop, and/or Databricks.
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Proficiency in Apache Airflow, ECS/EKS,Kafka, Docker, Terraform, and disaster recovery strategies. Oversee the implementation and use ofdata storage solutions, including PostgreSQL, MS SQL, Amazon RDS/Aurora,Databricks, and Snowflake.
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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.
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Two plus years working with one or more of the technologies: Kafka, API Gateway, Kinesis, Docker, Apache Airflow, and/or Lambda. Certifications in AWS DevOps, AWS RDS/DMS, data engineering, data science, automation, or database technologies are a plus.
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Apache Spark, Kafka, Airflow, Kubernetes, Databricks, Snowflake and more. Experience working with containerization platforms, such as Docker, EKS. Apache Spark, Kafka, Airflow, Kubernetes, Databricks, Snowflake and more.
$175,700 - $326,300 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience building robust large-scale data pipelines and storage solutions using Python, Pyspark, Databricks, Google/Azure clouds, WCNP, Apache Airflow, and other relevant tools. Experience with batch processing/scheduling frameworks like Apache Airflow, and event processing frameworks like Apache Kafka/Streams etc.
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