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Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
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7+ years of data engineering experience, including in senior and team leadership roles, at peer firms utilizing agile methods and modern SDLC processes to deliver quality technological solutions in a transparent, reliable way.
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Minimum of two (2) years of documented experience performing in a construction quality control management role on a heavy civil construction rail project. As a Quality Control Technician - Rail, you will play a critical role in the overall leadership and successful and timely delivery of complex multimillion-dollar fast-track, complex heavy-civil, highway and bridge projects from pre-construction stage through project execution and completion.
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And domain-led (e.g., role-based awareness) cyber risk mitigation initiatives in close collaboration with the Digital Risk Leader for ERP and Finance data domains, amongst others. Holistic oversight over cyber & data risks/security topics: setting the vision in line with global Cybersecurity and Data strategy, providing directions and support to relevant cyber & data security initiatives in the Governance domain and its satellite initiatives.
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Vertex is looking to hire a Quality Assurance Manager to join our Heme Patient Experience and Customer Operations (PECO) team. You will lead many aspects of the PECO Quality Assurance activities across PECO. As a subject matter expert, you will be responsible for playing a crucial role to ensure our team supports patients and HCPs in the best way, compliantly.
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You will partner closely with the leaders of Onyx’s engineering teams (DevOps and Infrastructure, AI/ML analysis and computing platform, data & knowledge platform, data engineering, UI/UX engineering), along with the Onyx portfolio management team, to deliver industry-leading Data Engineering products that power downstream consumption of petabytes of business-critical data.
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The successful candidate will join the Model Risk Management and Validation Group (MRM&V).
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Design, develop, and maintain data pipelines in Azure for ingesting, transforming, and loading data from various sources into centralized Azure data lakes and Databricks Delta Lake. Ensure data quality and integrity throughout the process.
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This entails designing and implementing a sophisticated data governance framework spanning across capabilities and tools such as data quality checks, defining/tracking KPI’s, data lineage and data structure and organization (e.g. organized data hierarchies, well-maintained data dictionary and report catalogue, as well as data and report certification.
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Establish robust data governance processes and standards to ensure the quality, integrity, and security of clinical trial data. Proficiency in statistical programming languages (e.g., SAS, R) and clinical data management systems (e.g., Medidata Rave, Oracle Clinical) is essential.
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Alternatively, the employer will accept a Master’s degree in Finance, Computer Science, Engineering Management, or other related field plus three (3) years of experience in the job offered or three (3) years as a Senior Application Support Engineer, Data Analyst, or a related occupation.
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Job DescriptionWe are looking for a Data Scientist to join our Risk Data Science and Analytics Team. You will improve our risk controls through advanced statistical and analytical techniques.
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Manages processes associated with data quality. 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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Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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Assist the team that will document, maintain, and tune AML transaction monitoring rules, sanctions screening systems, and risk scoring models as well as detailing data lineage and model/rule assumptions and parameters for all models.
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Title: data quality Company: Proactive Strategies in Cambridge, MA
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