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Undergraduate degree with 10+ years of Data Engineering experience with specific ETL Tools (e.g., DBT, Informatica, Data Stage, etc.) Bachelor of Engineering degree with 5-10+ years of Data Engineering experience with pertinent ETL tools (e.g., DBT, Informatica, Data Stage, etc.
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Experience in architecting data pipelines and solutions for both streaming and batch integrations using tools/frameworks like Glue ETL, Lambda, Google Cloud DataFlow, Azure Data Factory, Spark, Spark Streaming, etc.
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ETL/ELT : Databricks, SSIS, Azure Data Factory, Matillion , Alooma , Tale nd. Design End-to-end cloud data solutions including Architecture, Infrastructure, Storage, Data Model, ETL/ELT, and Consumption.
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SSIS, SQL / SSIS /SSRS, airflow, Control M, Autosys, Qlik view, Data stage, InformaticPython/Scala/PySparkReverse engineering of Legacy platformsMapping of Legacy models to CloudCloud migration experience from Legacy.
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This position is a blend of a senior architect and engineer - Data Migration of on-prem relational database into a cloud data lakehouse. Data Migration of on-prem relational database into a cloud data lakehouse.
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Our data engineering tech stack is primarily AWS running Spark/Scala within Databricks. The Data Engineering Manager is responsible for managing, coaching and mentoring a team of data engineers that will build data pipelines and data warehouse solutions to support business analytics.
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Drive ETL Process Innovation: Take charge of developing, optimizing, and maintaining robust ETL processes for data extraction, transformation, and loading, ensuring they meet evolving business needs.
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Experience with data integration tools (e.g., Informatica, Talend, Alteryx, SSIS etc) to carry out an ETL (Extract, Transform & Load) to move data from disparate systems to Master Data Management Hub.
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Experience in defining security for PaaS and IaaS implementations, such as system configuration, policy, tenant policy restrictions, access control, authentication (including federation), data at rest, and data in transit security.
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Knowledge of data connections to various databases and data transfer protocols. Analyze data and facilitate business process reviews in order to offer technical solutions that address the needs of the business.
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Strategize and execute Weisman Art Museum email marketing campaigns utilizing rich media and storytelling techniquesAdapt and evolve Weisman’s email strategy to attract new audiencesManage data extensions and lists in Salesforce Marketing CloudEngage with UMN Salesforce Marketing Cloud community to participate in ongoing training opportunities and to build strategic relationships across peer departments and organizations.
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Prepare data for regulatory submission in accordance to clinical data standards including Clinical Data Interchange Standards Consortium (CDISC), Clinical Data Acquisition Standards Harmonization (CDASH), and Study Data Tabulation Model (SDTM) for electronic submissions.
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Expertise in metadata management, ETL processing, reference data management. Deep expertise in design and implementation of enterprise data store, data warehouse, data governance, data quality management, real-time data ingestion, data modeling, and metadata management, in tools such as Azure Synapses or Snowflake.
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The ideal candidate will have healthcare data/AI experience and background in genomics and real-world evidence data studies. Build data science pipeline and platform capabilities for large-scale real-world evidence (RWE) studies and health economic analyses.
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Data visualization software (Power BI, Adobe Analytics, Excel, etc.) Validating tagging and usability within both Adobe Analytics UI as well as raw clickstream data – during feature releases as well as any necessary regression testing.
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data migration etl jobs in Minneapolis, MN
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