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Design and maintain datawarehouse systems such as big data processing solutions including but not limited to databricks, snowflake etc. If you are seeking a stimulating challenge, an opportunity for true ownership, and possess a background in overseeing extensive data engineering and operations, encompassing aspects such as real-time data acquisition, streaming data ingestion, data processing, large-scale data lake management, Enterprise Data Warehousing (EDW), and ensuring low-latency data delivery for both bussiness reporting and analytical use cases - then we are eager to connect with you.
$144,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Own the end-to-end architecture of the modern Safety/Pharmacovigilance Data Platforms which ingests data from the several systems across clinical, non-clinical systems and transforms it into insights for internal and external users using a scalable big data pipeline on GCP.
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Hands-on experience with big data processing frameworks like Apache Spark, Apache Hadoop, etc. Proven experience as a Data Engineer, Data Architect, or similar role with a focus on AWS technologies.
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Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). 16-18+ years of total experience in DWBI, Big Data, Cloud Technologies.
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Hands-on development experience with Design and Architecture of big data frameworks/tools: Azure Data Lake, Snowflake, Azure Data Bricks. Solid understanding of Snowflake computing, including its integration with Azure Data Lake, utilizing ADLS as a source for data processing.
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Should have prior experience in working as a Data Warehouse/Big Data Architect. Experience in logical & physical table design in Big Data environment to suite processing frameworks.
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Conduct transaction data analyses with big data technologies on Cloud platforms and turn massive amounts of data into actionable insights that drive business value: This involves analyzing large datasets using big data technologies like Spark on AWS EMR, Databricks, and Snowflake in the cloud, and transforming vast volumes of data into actionable insights that can inform business decisions.
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Extensive professional experience with Big Data systems, data pipelines and data processing. Practical hands-on experience with data technologies and Cloud Platform like Hadoop, Hive, Redshift, Big Query, Snowflake, Databricks, GCP and Azure.
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Demonstrated understanding of enterprise data warehouse, big data, BI & analytics, content management and data management. Facilitate the establishment and execution of the roadmap and vision for information delivery and management, including the enterprise data warehouse, big data, BI & analytics, content management and data management.
$65 - $70 an hourFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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The company has a mature data platform currently and Architect will be responsible for all new designs moving forward. The Architect will play a crucial role in designing, developing, and maintaining our data infrastructure and platform integration solutions.
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Specifically, this experience must be in writing Big Data data engineering jobs for large scale data integration in AWS. Prior experience in writing Machine Learning data pipeline using Spark programming language is an added advantage.
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Knowledge of data architecture, big data architectures, experience of building solutions on Azure, AWS, GCP, Multi-threaded data processing on CPU and GPU architectures.
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SKill: Big Data Architect, Cloudera Big Data Tool stack (Hive ,Impala, OoZie), Pyspark, Teradata, Shell Script, Unix programing, Hadoop 8+ years of data engineering/architecture experience in Waterfall and Agile Methodology, with a proven track record of delivering complex data solutions, preferably in the financial sector.
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Experience with Big Data technologies such as Hadoop, Spark, or related platforms for data processing and analytics. Architect and design scalable, high-performance Java applications, utilizing Python for specific back-end tasks and data processing.
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Strong experience working on Databricks, DBT and data visualization tools like Power BIStrong knowledge of database technologies, ETL processes, cloud platforms, and big data technologies.
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big data architect processing jobs Title: architect
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