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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. Kubernetes, Python, SQL, Pyspark, GCP, Azure, and Kubernetes.
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Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.) Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.
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Strong proficiency in Microsoft Azure and Google Stack technologies, particularly Azure Data Services, Azure Synapse Analytics, Google BigQuery, Google Cloud Dataflow, etc.
$168,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. SnowFlake,Netezza, Teradata, AWS Redshift, Google BigQuery, Azure Data Warehouse, or similar). 3+ years' of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M.
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Experience in one of the public cloud providers – GCP, Azure, AWS.Experience with relational SQL and NoSQL databases, including Postgres and MongoDB.Experience with workflow management tools: Airflow, AWS data pipeline, Google Cloud Composer, etc.
$77,400 - $160,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Azure Synapse/Bigquery/Redshift experience is good to have. Azure Synapse/Bigquery/Redshift is good to have. Azure Synapse/Bigquery/Redshift experience is good to have. Azure Synapse/Bigquery/Redshift is good to have.
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Familiarity with Hadoop, Spark, and Cloud databases (Snowflake, BigQuery, Redshift, Databricks) and stream processing frameworks (Kafka, Kinesis). Proficient in Big Data, Distributed Systems, and Cloud Architectures (AWS, Azure, GCP.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Experience with real-time and streaming technology (i.e. Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming etc.
$124,372.5 - $247,200 a yearFull-timeExpandUpdated Yesterday - UpvoteDownvoteShare Job
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Active contributor to one or more PAAS platforms software such as, Snowflake, Databricks, Confluent, Google BigQuery, Spanner, Redshift, Aurora, Cosmos DB, Redis, MongoDB, ElasticCloud, CockroachDB, Yugabyte, Hashicorp, etc.
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Expertise in working with diverse data warehousing solutions, such as Snowflake, Redshift, BigQuery, and DataBricks, as well as databases like Postgres and MySQL. - Hands-on experience in configuring and deploying containerized services utilizing Docker and Kubernetes, across leading cloud service providers such as AWS, Azure, and GCP.
Full-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Data warehousing experience on platforms like BigQuery and Azure. FanIQ partners with teams, schools, festivals, and venues to create custom content for use on social media platforms like Snap, TikTok, Meta, and Pinterest.
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Experience with data warehousing concepts and tools (e.g., Snowflake, BigQuery) is a plus. Job Title: Big Data Engineer with azure. Familiarity with cloud-based data platforms (e.g. Azure.
Full-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Knowledge of distributed databases such as Redshift, Snowflake, Azure Synapse, and BigQuery. Experience with cloud based data services offered by Azure, AWS and Google. Knowledge of distributed databases such as Redshift, Snowflake, Azure Synapse, and BigQuery.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Experience with Cloud Services (AWS, Google Cloud, Microsoft Azure, etc). Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc.
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Cloud Data Warehouse (Redshift, BigQuery, Azure, Snowflake) One year of experience using Cloud Based Platforms (e.g. Azure, AWS, GCP) to complete advanced data processing, including implementing data pipelines for structured and unstructured data.
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