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Knowledge of data and application integration/middleware tools such as SnapLogic, Informatica, Webmethods, Tibco, SSIS, etc. Hands-on experience designing, implementing and troubleshooting integration/ETL solutions using wide variety of data sources and targets.
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As an Information Architect , you will deliver innovative data management, integration, and streaming platforms to underpin cutting-edge drug discovery processes. Use your technical skills to extend and enrich data management platforms to support new modalities, e.g., Gene Therapy, Proteomics, Functional Genomics and more.
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You will be joining as a Principal Systems Integration Engineer/Scientist in the Applications Development team and be responsible for integrating genomic applications on the Volta Labs fluidics platform and contributing to internal process improvements.
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Work closely with scientists within the in-vivo pharmacology group to verify in-vivo and Pharmacodynamic (qPCR) data. Work closely with scientists within the ADME group to verify bioanalytical data generated using HPLC-FD and LC-MS/MS.
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Designs and implements data integration solutions in support of business requirements. Demonstrated Expertise (“DE”) designing, developing, testing, and implementing enterprise analytics platforms into Snowflake using Control-M jobs, Apachi Nifi, Apache Kafka, JavaScript, SnowScript, and Snowflake Tasks; and deploying data migration conversion scripts using GIT, Bit Bucket, and Jenkins Core pipelines.
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At least 4 years of experience in Spring, GIT, JIRA/Confluence, CI Tools, API GatewaysGood knowledge of Splunk, AppDynamics, Git, Nexus and their integration with Cloud platformKnowledge of Performance EngineeringGood knowledge on Web Servers, Application ServersKnowledge of design principlesAbility to manage technology and performance engineeringGood analytical skills and data analysis capabilities.
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Minimum of 4 years of hands on development and architect of data warehouses, ETL, data integration, MDM etc. Knowledge of data management capabilities (data governance, data quality, metadata management, master data management, data lifecycle management and data lineage.
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Our solution integrates cutting-edge cancer research and clinical data to empower clinicians in tailoring optimal treatment strategies for individual patients. Laboratory Automation : Strong understanding of laboratory automation principles and technologies, including robotic systems, instrumentation, and integration with laboratory information management systems (LIMS.
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Radar Receiver Exciter integration and test engineers are the liaisons between many Radar system components and are responsible for Radar Receiver Exciter data analysis and calibration, integration of hardware with firmware and software, and resolving system level issues that may stem from software or hardware anomalies.
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The Data and Presentation Specialist role provides substantial exposure to how GMO communicates with clients and prospects about our investment strategies. The Presentation and Data Specialist is responsible for the coordination and production of product and fund materials; and,providing input and requirements on new systems or technology enhancements related to these materials.
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Design and build data solutions using Databricks, SQL, Python, Spark, and Delta Lake in the Azure ecosystem (Blob Storage, Data Factory, Event Hubs). Collaborate with engineers, product, and business leaders to ensure data platform is integrated with other systems and technologies (Tableau, Power BI, APIs, custom applications.
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Work with data integration teams to ensure seamless data flow between various systems and databases within the project, maintaining data integrity and consistency. Understanding of data integration technologies and tools, including ETL processes and data integration platforms.
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Familiarity with regulatory guidelines and standards related to bioanalytical data review. Interpret data and provide insight for in-vivo studies, ensuring alignment with study objectives and protocols.
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Vendor certification (Azure Data Engineering, PowerBI certifications, Snowflake Certifications.) Utilize experience on various BI and data tools like PowerBI, Azure Data Engineering methodologies (ASQL, ADF, ADL, Logicapp, etc.
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Experience with API development and microservices architecture (REST, GraphQL), RESTful service consumption and integration, Kafka or data streaming platforms. Data science ML engineering background preferred.
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