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Databases: Proficiency in Oracle, Snowflake, and Databricks. Design efficient data synchronization processes between on-premises Oracle databases and Snowflake using Kafka and CDC extraction tools.
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Data Management concepts and standards (SQL Server, Oracle, Cloud, Snowflake, Azure, etc.) Technology : Azure ADF/ ADB, Snowflake + Any BI Tools ( Tableau / Qlik) + AI/Client , GenAI.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, GCP, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, Google Cloud Platform, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
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Cloud Platforms: Knowledge of cloud infrastructure and services,preferablyAzure, as it relates to Snowflake and Databricks integration. Utilize Snowflake and Databricks for advanced reporting and analytics, providing actionable business insights.
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Data movement (real-time replication or ETL/ELT), multiple clouds (AWS, Azure Google, Alibaba), cloud analytics destinations (Snowflake, Databricks, Kafka, RDS, Synapse, BigQuery, etc.) Experience in databases (Oracle, SQL Server, PostgreSQL, etc.
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Databricks Certifications (ie: Data Engineer Associate; Data Engineer Professional, Machine Learning Associate, Machine Learning Professional) AI&DE24 Databricks Cloud Engineer, Sr. Consultant. Experience with Databricks Unity Catalog.
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You will be part of a team of developers, analysts, SMEs, and architects designing and building Snowflake data warehouses and analytical solutions which draw from legacy and modern data sources stored in various cloud and on-premises databases such as Oracle and Salesforce.com. You will leverage tools such as DBT, FiveTran, Coalesce, AirByte, Airflow and GitHub to develop the next generation data mesh platform for CDK Global LLC.
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5+ years experience in field of data engineering involving building data integration solutions or data warehouse environments such as AWS, Snowflake, Oracle, etc. Design and build Data Lake and data warehouse solutions on Snowflake and AWS using streaming and batch processes.
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2+ years experience implementing data solutions on the Databricks Data Intelligence platform, to include Delta Lakes. Experience with Cloud using Amazon Web Services (AWS), Microsoft Azure, and/or Google Cloud Platform (Google Cloud Platform.
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Experience with Databricks. We serve as a trusted advisor and managed service provider bringing a mix of capability and capacity across data modernization, data ops, AI, and ML. Through our unrivaled breadth and depth of services across every major industry and domain, we help our clients run smarter, faster, and more efficiently.
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With 99.9% uptime and self-healing pipelines, Fivetran enables thousands of leading brands across the globe, including Autodesk, Condé Nast, JetBlue, Lufthansa, Morgan Stanley and Pitney Bowes, to accelerate data-driven decisions and drive business growth.
$160,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Expert level SQL knowledge on databases such as but not limited to Snowflake, Netezza, Oracle, Sql Server, MySQL, Teradata. Build and automate the data ingestion, transformation and aggregation pipelines using Azure Data Factory, Databricks / Spark, Snowflake, Kafka as well as Enterprise Scheduler tools such as CA Workload automation or Control M.
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Hands on working experience is a plus Must have : Snowflake Architecture Snowflake : snowsqlsnowpipe , semi structured data loadAVRO, PARQUETNDM, sFTP , Datarouter(Any One)Python ProgrammingSpark/Databricks(Any One)Kafka, Ni-fi(Any One)Cloud (AWS/Azure/GCP)(Any One) NOTE: Only Developer ,no support profile required.
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Experience in SQL (SQL Server, Oracle, MySQL, BigQuery, Snowflake) Hands-on experience with one of these - BigQuery, Snowflake or Amazon Redshift. and data pipeline orchestration (e.g., Airflow, Astronomer, DBT cloud, etc.
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