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Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets.
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The Head of R&D Automation platform is responsible for leading the technical design, implementation, testing and deployment of automated processes to accelerate Takeda's portfolio starting with preclinical research and ending with submission with the objective to improve efficiency and data quality across the entire business and data flow.
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Understanding of SOA, Data integration, Data Quality, data architecture and Master Data Management, project life cycle Phases, best practices and processes. Experience in integrating data quality & ETL tools with MDM hub will be a plus.
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An understanding of ETL concepts including the data integration pipeline, staging tables, incremental loading, SCD, data quality, business logic, and views. Experience authoring SQL to query, load, transform, and retrieve data from various databases including MS SQL Server, Redshift, and PostgreSQL.
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Experience with modern data engineering tools such as Talend, DBT, Databricks, Snowflake and data visualization tools such as PowerBI, Tableau, ThoughtSpot. Deep understanding and proven experience in Databricks, Azure Data Factory, Synapse.
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You will leverage your expertise in data analysis, healthcare informatics, and project management to develop innovative solutions that optimize patient care and improve overall quality outcomes.
$140,000 - $185,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Maintain and curate data documentation including Architectural Decision Records (ADR), how-to guides, data lineage and ownership using Azure DevOps or similar tool. Using the Cloud OTI Data Platform, the Senior Data Engineer will build highly available, robust, concrete data pipelines and reporting solutions following industry best practices, adhering to OTI security guidelines, modifying, and running automated CI/CD pipelines used for releasing code, and modifying and executing terraform modules for deploying infrastructure components, working collaboratively under the direction of OTI data engineering management and leads.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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Including hands on experience with productionized data ingestion and processing pipelines using T-SQL, SSIS, Python, Data bricks, Snow SQL. Minimum 5 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse.
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As a Data Science and Generative AI (GenAI) Specialist, it will be your responsibility to engage early with M&E executives and develop strategies as they look to harness complex data sets to drive value across their media business from content production to distribution.
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Ensure data quality and integrity throughout the data lifecycle. 5+ years of experience in data engineering with Databricks and Spark. We are looking for a data engineer who has strong experience in building scalable and reliable data pipelines using Databricks and Spark.
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Create and maintain highly scalable data pipelines across Azure Data Lake Storage, and Azure Synapse using Data Factory, Databricks and Apache Spark/Scala. 7 years of experience implementing analytics data Solutions leveraging Azure Data Factory, Databricks, Logic Apps, ML Studio, Data Lake, Synapse, Informatica Power Center, and Oracle.
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Mandatory Skills : Azure Databricks, Azure data lake , Ansible, SQL, Terraform, Snowflake, Kafka , Azure CLI, Databricks CLI, PowerShell and/or Bash. Architecting, deploying, managing, and supporting Azure Databricks, Azure Data lake and related solutions.
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Handling raw data ingestion through Delta Live Tables while ensuring data quality and access latency. Ensuring data security and compliance in Databricks and Snowflake environments.
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Develop data quality rules for Key Data Elements Integrity controls to publish End User Dashboard with Data Quality results to comply with regulatory mandates. Develop quality standards to ensure data quality and integrity across various database systems.
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data quality jobs Title: data specialist Company: Deloitte in Hoboken, NJ
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