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Writing Scala code with tools like Apache Spark + Apache Arrow + Apache Kafka to build a hosted, multi-cluster data warehouse for Web3. 6+ years experience engineering software and data platforms / enterprise-scale data warehouses, preferably with knowledge of open source Apache stack (especially Apache Spark, Apache Arrow, Kafka, and others.
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5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg.
$268,000 - $414,000 a yearFull-timeExpandApply NowActive JobUpdated 83 days ago - UpvoteDownvoteShare Job
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Experience in data engineering or integration roles with a focus on Python, Spark, and Databricks. Design and architect data integration solutions to connect various data sources and systems using Python, Spark, and Databricks.
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As a Data Engineer for our Data Platform Engineering team you will join skilled Scala/ Spark engineers and core database developers responsible for developing hosted cloud analytics infrastructure (Apache Spark-based), distributed SQL processing.
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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. High level of proficiency in ETL processes and demonstrated, hands-on experience with technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Direct hands on experience with highly scalable data pipelines using BigData technologies (Spark, Hive, Airflow, DBT, Parquet / ORC, Kafka / Streaming, etc) Distributed Compute: Spark/Databricks.
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Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably in Databricks). Designing and implementing highly performant data pipelines from multiple sources using Apache Spark and/or Azure Databricks.
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Your expertise in Apache Spark (Scala), Apache Airflow, AWS Glue, Python, Kubernetes, and Oracle will be crucial in ensuring efficient data processing, storage, and retrieval. Design, develop, and deploy robust data pipelines and workflows using Apache Spark (Scala) and Apache Airflow to support data processing and transformation activities.
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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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Familiarity with data integration techniques, ETL frameworks (e.g., Apache Spark), and workflow management tools (e.g., Airflow). blob storage, Redshift, Kafka, Hadoop, Spark, Hive etc. Familiarity with data integration techniques, ETL frameworks (e.g., Apache Spark), and workflow management tools (e.g., Airflow.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks. hands-on experience with technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Extensive hands-on experience implementing data migration and data processing using AWS services: VPC/SG, EC2, S3, Autoscaling, CloudFormation, LakeFormation, DMS, Kinesis, Kafka, Nifi, CDC processing Redshift, Snowflake, RDS, Aurora, Neptune, DynamoDB, Cloudtrail, CloudWatch, Docker, Lambda, Spark, Glue, Sage Maker, AI/Client, API GW, etc.
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Micro-batch streaming and continuous streaming process in Databricks for high latency, low latency and ultra-low latency of data accordingly by using inbuilt Apache spark modules. Strong hands-on expertise in building Data engineering solutions using Java, Apache Spark and Scala.
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We are seeking a Senior Data Architect with extensive experience in Databricks, Spark, Python, and ETL technologies to join our dynamic team. Leading the architecture and implementation of Spark and Databricks-based ETL frameworks for large-scale enterprise systems.
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spark job Title: assistant Company: Boys And Girls Club Of Bluffton
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