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The Data Operations Manager will also work closely with Engineering, Analytics and Product Management teams, in providing actionable insights and support for strategic initiatives along with building powerful tools for taxonomy administration.
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Build highly collaborative relationships with MABI Insights and Analytics, MABI Market Access, MABI Data Capabilities COE, Digital Lab, Finance/Forecasting, MABI Patient Services, Sales Operations, AbbVie Innovation team, Consumer marketing team, AbbVie GCD and Marketing/Sales leadership.
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Oversees the day-to-day operations, personnel management, qualityimprovement, and strategic planning for data operations including availability andsecurity of data assets. Develops and implements strategies to enhance theperformance and capabilities of Data Operations.
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1+ years of work experience as an Operations Data Analyst preferred. The Delegated team (an outsource chief investment officer unit) of Aon Hewitt Investment Consulting is currently seeking a Data Analyst to join the team.
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Advise the Senior Manager – Data Center Operations in the development and supervision of the facility maintenance program and equipment/system operation. The Manager - Data Center Operations is responsible for employee training and ensuring all staff is adequately qualified to perform required duties.
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Leading a high-performing team comprised of the Merchandise Manager along with Beauty Advisors and Task Associates, you will have overall responsibility for all aspects of store operations, including realignments, planograms and inventory life cycle-related processes.
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Databases: Oracle, MS SQL Server, Azure PostgreSQL, Denodo - SQL: design and develop complex SQL queries, stored procedures, views, or to tune existing ones for optimal performance - Programming: Python, R - Azure Cloud - Azure Databricks - ETL Tools: Azure Data Factory, IBM DataStage etc.
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We’re actively seeking a talented Investment Operations Data Analyst to join our Investment Operations team in Newport Beach, CA. This role can be on-site or potentially 100% remote.
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Data Scientists are expected to use statistical techniques to help test teams make better decisions and improve their operations. Working Knowledge of data pipeline and ETL tools (Apache Airflow, Databricks, Apache NiFi, Azure Data Factory, etc.
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This position offers a competitive compensation package including a base salary, bonuses, healthcare and many other bells and whistles.
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Requirements EDUCATION Bachelor’s degree in Math, Science, Statistics, Economics, Finance, Informatics, Computer Science, Information Systems, Health Information, Epidemiology, Data Analytics, Data Science, Predictive Analytics, Artificial Intelligence, Engineering, or Physics required.
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Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Build high-performing data processing frameworks leveraging Google Cloud Platform and utilizing GCP Services like Big Query, Python, Composer, Dataflow, GKE, Pub-Sub, Cloud Monitoring. As a member of the Data and Analytics organization, you will be responsible for designing, building, and maintaining best-in-class data engineering pipelines aimed at driving best-in-class solutions primarily using Cloud platforms like GCP. You will collaborate with cross-functional teams, including data scientists, analysts, business SME’s and software engineers, to ensure the efficient and reliable processing, storage, and retrieval of data.
$72,100 - $144,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficiency in SQL and experience working with relational databases (e.g., PostgreSQL, MySQL) and data warehousing solutions (e.g., Redshift, BigQuery). Experience with data visualization tools such as Tableau, Looker, or Power BI, and proficiency in data manipulation and visualization techniques.
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ExposureMinimum 5+ years of experience Worked on large Data Engineering initiatives from start to finishFormal ETL tooling (Informatica, DataStage, etc.) Azure experience (not just a “cloud engineer” or just using services but more on data / migration side and creating pipelines etc.
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Title: data operations Company: Canoe Intelligence
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