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Airflow & Prefect for ETL. Google Cloud Platform: BigQuery, Dataflow, and Composer. Looker, Amplitude, & Tableau for data visualization. Experience with a BI tool such as Looker or Tableau. Airflow & Prefect for ETL.
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Experience with R, Python and Spark. Hands-on experience with at least one big data tool (Databricks, Synapse, Redshift, Snowflake, Hadoop, etc.) To ensure you the most convenient IT experience, we offer top-quality strategy consulting, custom software development, eCommerce, omnichannel, mobile banking, technology consulting, Progress OpenEdge, managed cloud, data analytics, and B2G solutions.
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Data Architecture Leadership : Lead the design, implementation and operation of robust data architecture, ETL/ELT pipelines, and data warehousing strategies using Airflow and AWS cloud services.
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Experience testing 'big data' solutions and data pipelines (Snowflake, Hadoop, Spark, Presto, etc.) Experience testing 'big data' solutions and data pipelines (Snowflake, Hadoop, Spark, Presto, etc.
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Hands-on experience with data processing frameworks like Apache Spark or Apache Flink. Design, develop, and maintain scalable data pipelines, ETL processes, and data warehouses to support data ingestion, transformation, and storage.
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Proficient with big data tools, such as Spark, Snowflake, or Databricks. Proficient with big data tools, such as Spark, Snowflake, or Databricks. As a Director of Engineering, you will seamlessly combine industry knowledge, innovative vision, emotional intelligence, thought leadership, and a solutions-driven approach to promote excellence in alignment with CoPilot AI’s people-first culture.
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Extract Transform Load (ETL) and streaming experience using Spark, Kafka, Hive, Iceberg, or similar technologies at petabyte scale. A successful candidate will have experience building data pipelines using varied engineering technologies such as AWS, EMR, EKS, Spark, Hive, SQL, Iceberg, Snowflake, Oracle, Airflow, Datadog.
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Big Data Technologies: Apache Spark, Hadoop, Kafka. Big Data Technologies: Apache Spark, Hadoop, Kafka. Drives to exceed expectations in alignment with our BFS SPICE values. Data Warehousing: Data Bricks, Snowflake, Amazon Redshift, SAP HANA.
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Je hebt kennis en passie voor het optimaliseren van ETL-processen en het gestructureerd ontsluiten van data met behulp van tools zoals Azure Data Factory, Snowflake, Databricks en/of Microsoft SQL Server.
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Familiarity with big data tools & distributed systems (spark, redshift, kafka) Databases: SQL querying & db understanding (RDBMS: mysql, postgresql; Nosql: mongodb, elasticsearch, dynamodb) Django/Flask (preferred, must be experienced in building APIs.
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Familiarity with data processing and ETL tools such as Airflow, Snowflake, Postgres, Kafka, and Redis. Familiarity with data processing and ETL tools such as Airflow, Snowflake, Postgres, Kafka, and Redis.
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We are a dynamic team of talented developers and architects who partner with business areas and other technology teams to deliver high profile projects using a raft of technologies that are fit for purpose (Java, Cloud computing, HDFS, Spark, S3, ReactJS, Sybase IQ, Snowflake, Tableau among many others.
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Proficiency in Kubernetes for container orchestration and Kafka or Apache Spark for real-time data processing and streaming. Proficiency in Kubernetes for container orchestration and Kafka or Apache Spark for real-time data processing and streaming.
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Experience with big data technologies (e.g., Apache Spark, Hadoop) and data processing frameworks. Experience with big data technologies (e.g., Apache Spark, Hadoop) and data processing frameworks.
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Hadoop, Spark, etc., as well as streaming data architectures based on Kafka, Kinesis, etc., and orchestration tools. Becoming familiar with precision medicine, genotyping and the latest in cancer research.
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spark etl jobs in Snowflake, AZ
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