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Script and execute tests for back-end testing - ETL,warehousing, Databases, APIs. Test Cloud Infrastructure – Instances, Loadbalancers, Gateways, Security Domains by Implementing TOSCA, qTest, NeoLoad andother Testing and reporting tools.
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You likely have experience with a variety of architectures, patterns, and methodologies focused on Analytics Strategy, Data Governance & Master Data Management, Data Architecture(s), Distributed Systems, ETL, Big Data, IoT, Data Visualization and Analytics.
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Knowledge of data warehousing architectures, data integration techniques, and ETL tools (e.g., Informatica, Talend, Apache NiFi). Design, develop, and maintain data pipelines and ETL (Extract, Transform, Load) processes to ingest, process, and transform healthcare data from diverse sources, including electronic health records (EHRs), medical imaging data, wearable devices, and claims data.
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The Data Warehouse Architect role involves strategically designing and implementing data warehouses, data marts, and data stores as well as requisite ETL (Extract, Transform, Load) and visualization (reporting) development while ensuring high levels of data availability.
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Strong skills in languages such as Python, R, SQL or Scala, alongside experience of using modern and traditional data technologies including: ElasticSearch, MongoDB, PostgreSQL, mySQL/mariaDB, Oracle, SQL Server, Hadoop, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies.
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Strong understanding of data modeling, ETL/ELT processes, data integration techniques, and data warehousing concepts. Azure, ADF, Databricks, Data Factory, ADLS KeyVault, Terraform, Azure DevOps, DBT.
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Ideal candidates have 2+ years of Boomi ETL experience, knowledge of SQL/PL-SQL, and data warehousing. We are looking for a Boomi ETL Developer that can work hybrid (would consider fully remote for a Boomi SME) to create and manage reporting solutions for various departments.
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You have experience with ETL/ELT and data warehousing using tools such as dbt, Azure Data Factory, Matillion and/or Fivetran. Supporting self-service data pipeline management (ETL) and self-directed learning process.
$140,000 - $155,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Knowledge of data engineering and data warehousing concepts, including RedShift, Redshift Spectrum, AWS Glue, AWS Lambda. Experience with Databricks, Reverse ETL. Proficient in programming languages such as Python, R, SQL, and SAS.
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You will develop ETL pipelines, work with data sources, and ensure data accuracy. You will develop ETL pipelines, work with data sources, and ensure data accuracy.
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Google Cloud Platform - Data Engineering - Data Warehousing - Data Modeling - RDBMS - SQL - Python - ETL. Perform ETL activities and assist with customer inquiries and incident resolution.
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Hands-on experience with ETL tools, data lakes, and data warehousing solutions (Snowflake, Redshift, BigQuery, etc. Hands-on experience with ETL tools, data lakes, and data warehousing solutions (Snowflake, Redshift, BigQuery, etc.
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Minimum 10 years of experience in data governance, data engineering, and data strategy, with a focus on leadership roles. Ensure a firm wide partnership and commitment across the functions for data architecture, data engineering, data governance and data quality.
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Deep understanding of data engineering principles and best practices, including data modeling, ETL/ELT processes, data warehousing, and data governance. Strong knowledge of cloud platforms (e.g. AWS, Azure, GCP) and associated data services (e.g. Redshift, Data Factory, BigQuery.
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7+ years of hands-on Microsoft Power BI, Azure Synapse, and Data Factory, Data Warehouse, ETL, SQL Server, Informatica and BI development. Experience with a variety of business intelligence tools and applications, such data visualization, data mining and analytics, ETL/EDW, data processing, and data storage tools.
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