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You have at least 4 (but ideally more) years of hands-on experience with data modeling, schema design, data operations, and data warehousing. You have deep experience creating data warehouses using Timescale, Snowflake, and/or BigQuery, and you also bring experience using DevOps tools and solutions like Docker, CI/CD, and AWS.
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The Sportsbook team here at Penn is responsible for working hand-in-hand with our Data Science, Engineering, and Data teams to support efficient development and deployment of models, forecasts, and simulations to help improve theScore Bet and ESPN Bet. Our team values creativity, collaboration, ingenuity, and ownership.
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Essential Functions:Develop a clear understanding of the data needs and uses as relates to the specific application as well as the larger context within which data is needed and used in by CBH.Develop new custom QuickBase applications to meet the various business needs, focusing on data capture applications with the understanding that the data will be governed and will need to eventually be consumed by a CBH reporting database layer and/or CBH Data Warehouse environment.
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Comfortable with basic data science, data visualizations, and analytical products (Tableau, Looker, Mode Analytics) Interface with a broad peer group including product managers, machine learning engineers, computer vision engineers, and data pipeline engineers.
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The position will work closely with the members of the clinical research team to develop effective tools for close monitor and reporting of trials accrual, and coordinate the timely study activation and submission of protocol amendments.
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The team's scope covers data pipeline development, search infrastructure, web scraping, detection algorithms, internal toolings and data quality. Alt's compensation package includes a competitive base salary benchmarked against real-time market data, as well as equity for all full-time roles.
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Position Overview: The QuickBase Applications Developer ensures successful implementation of QuickBase software technology within CBH for data capture, workflow management, and other internal CBH and external CBH partner applications.
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Cloud-based Big Data/MPP analytics platforms like Snowflake, AWS Redshift, Google BigQuery, Azure Data Warehouse. Workflow management engines like Dagster, Airflow, Google Cloud Composer, AWS Step Functions, Azure Data Factory or similar.
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Plus, our team brings over 25+ years of combined experience building provider data systems at Oscar Health, and we're backed by top-tier VC firms who share our bold vision of creating a one-of-a-kind healthcare cloud that eliminates friction surrounding provider data.
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Technical Skills: Proficiency in programming languages such as Python, R, or SQL. Experience with data visualization tools (e.g., Tableau, Power BI, Looker Studio, D3. Familiarity with AI frameworks and tools such as TensorFlow, PyTorch, and OpenAI. Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud, Azure.
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We are looking for a AWS Infrastructure & DevOps Engineer who will contribute to design, implement, and maintain of our cloud infrastructure on AWS. The ideal candidate will have expertise in Terraform, Bitbucket Pipelines, Snowflake Data Warehouse, AWS Lambda functions, and various AWS services including SNS, SQS, SES, API Gateway, EC2, Textract, Bedrock and managed Airflow.
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You've used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way. This globally-distributed team of senior engineers is responsible for building new analytics and geospatial capabilities in Elasticsearch, profiling and optimizing existing functionalities, analyzing runtime and edge-case behaviors of distributed algorithms, and innovating new ways to store and analyze data in Elasticsearch.
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Proficient writing optimized GCP BigQuery SQL data translation queries and scripts. The Sr Cloud Data Engineer will integrate a new vendor platform into our Google Cloud Platform (GCP) Enterprise Data Warehouse (EDW.
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Hands-on experience and knowledge of data lake technologies (Databricks, Snowflake, etc),data storage formats (Parquet, Avro etc.) 7+ years of experience in data strategy, data architecture, modeling, solution design, data engineering, or a similar role.
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Knowledge of data warehousing concepts and experience with tools like Redshift, BigQuery, or Snowflake. Hands-on experience with big data technologies such as Hadoop, Spark, or similar frameworks.
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clinical trials data jobs Title: operations Company: Boston Pharmaceuticals in Philadelphia, PA
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