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End-to-end supply chain of data including, but not limited to, AI and Advanced Analytics, Business Intelligence, Cloud enablement, Data Privacy, Data Science, Digital Transformation, Data Governance / Data Management, Enterprise Data Architecture, RPA/Intelligent Automation, Risk and Regulatory Compliance.
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The candidate will be an intellectual, smart, with a developer mindset and interest in developing enterprise scale web-based solutions using industry recognized cloud platforms (MS Azure or AWS or similar), backend (SQL, SSIS, Data Factory) and Big Data Tech (Spark, Databricks, Parquet, Kafka, etc.
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The firm is the No. 1 investment bank for all global M&A transactions, the No. 1 M&A advisor for the past nine consecutive years in the U.S., the No. 1 global restructuring advisor for the past ten consecutive years, and the No. 1 global M&A fairness opinion advisor over the past 25 years, all based on number of transactions and according to data provided by LSEG (formerly Refinitiv.
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Responsible for logging and accessioning all diagnostic cases submitted to Neuropathology into various LIS systems; EPIC and Neuropathology database; and generate computer data sheets; scan incoming generated slides into the Vantage specimen tracking eSystem and generate preliminary reports to match and distribute slides to the appropriate faculty on service.
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Work with developing and deploying data infrastructure and integrations in the cloud including data warehouse like snowflake, redshift etc. Develop ETL integrations with Snowflake - Data extraction, transforming and loading.
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Proven experience as a Technical Lead with a focus on Databricks and big data technologies on Azure Cloud Platform. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Azure Integration: Work with Azure services such as Azure Data Factory, Azure Databricks, and Azure SQL Database for data integration, processing, and storage. We are seeking a skilled Data Engineer with extensive experience in DBT, Snowflake, and Azure, along with proficiency in Python and SQL. The ideal candidate will have a strong understanding of data modeling principles and a proven track record of developing robust data pipelines and architectures.
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As a Power BI Developer, you will be responsible for designing, developing, and maintaining business intelligence solutions using Microsoft Power BI. A successful candidate will work closely with stakeholders to understand business requirements, create interactive and insightful reports and dashboards, and contribute to data-driven decision-making within the organization.
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Data warehouses and file stores such as Snowflake, RedShift, Teradata, BigQuery, Amazon S3, Amazon RDS, Azure Synapse, Databricks Lakehouse, etc. MS, or PhD in Computer Science, Computational Mathematics, Applied Mathematics, Engineering, Data Science, Statistics or equivalent.
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5+ years of relevant experience, which could include working in operational risk or data governance function in engineering/finance/risk divisions of financial institutions or working in data management reliant regulatory reporting such as BCBS239, Basel 3 or CCAR in financial institutions or working the data management /regulatory implementation practices in consulting organizations.
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Experience - Minimum of ten (10) years of data experience in any combination of the following: Epic Cogito (Radar, Reporting Workbench, SlicerDicer, Epic Analytics Catalog, and their data warehouses: Clarity, Caboodle, Chronicles) Microsoft Azure cloud/Fabric, Synapse, Purview, Power Products (Power BI, Power Apps, Power Automate, Power Pages.
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Certification in cloud computing (e.g., AWS Certified Solutions Architect, Azure Data Engineer Associate, Google Cloud Certified - Professional Data Engineer). Title: Data Engineer - Remote.
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Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai.
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Experience with common data languages (e.g., Python, Scala) and data warehouses (e.g., Redshift, BigQuery, Snowflake, Databricks) 1+ Managing a cloud-based data environment that has complex platform integration and orchestration using tools like AWS, Airflow, Talend, RedShift, or similar.
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data job Title: administrative assistant Company: Summit County in Dallas, TX
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