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Hands on experience with modern cloud data warehouse and engineering for one or more of the following cloud providers - GCP (Big Query, Vertex, Cognitive Services), Snowflake, Azure (Synapse, Dynamo, Cosmos, Azure ML, Power BI), AWS (Redshift, Sage maker), Tableau;Possessing a certification(s) in one of the following is a big plus – GCP/AWS/Azure/ data or ML engineering.
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Candidate will be given the opportunity to learn and make use of sophisticated tools (SQL, Alteryx, Informatica, SAS, Tableau, SSRS, DataRobot etc) and technologies (Big data like Hadoop, Python/R Programming, AI/Data Science,) to provide customized automated solutions across multiple business segments.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets.
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Experience with Azure Synapse, Databricks, ADLS Gen 2, Google Analytics, Firebase, Big Query, Event Hubs, Kafka, Salesforce, SAP, and CDP platforms. Data Evangelist: Promote data product adoption through training and webinars.
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Big data technologies like Hadoop (Hortwonworks, Cloudera, Azure HDInsight, Amazon EMR), Spark, Kafka, Elasticsearch and others; e web, service, data, and infrastructure) and insurance specific (i.e. Guidewire, EIS, Duck Creek, etc.
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Familiarity with big data / visualization tools such as PowerBI, Tableau and the core concepts of relational data. Interprets data to identify trends, patterns, and insights to recommend business decisions.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Some experience with cloud-based and on-prem data solutions (Apache Hadoop, Datastore, Firestore, Cloudera Data Platform, Big Query, Azure SQL, Cosmos DB, Red Shift, Apache Spark, ElastiCache, CloudSQL, Data Bricks, Snowflake, Apache Arrow, Apache Airflow, Flink.
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Softrams is a Maryland and Virginia-based small business information technology, consulting, and solutions provider specializing in emerging technologies for UX/UI, mobile apps, DevOps, big data analytics, data science, and cyber security.
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Derek Bang, the practice founder and inventor of the group’s flagship software product for net revenue reporting, Revenue Cycle Analytics (RCA) came to Crowe nearly 20 years ago with an idea for a strategic pursuit in the Healthcare Industry through his previous experience as a Healthcare Auditor at a Big 4 firm.
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Knowledge and use of statistical packages such as SQL, SAS, Python, or other tools to mine,and extract complex consumer and transaction level data on big data and/or cloud computing platforms.
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Expert in cloud infrastructure management, including IaC, monitoring, and big data technologies. Lead the design, development, and deployment of ML model pipelines, in collaboration with Data Science and Data Engineering teams.
$265,200 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience with Databricks or similar big data processing platforms is a strong plus. Experience with and understanding of Data Lakehouse Architecture, big data processing, and related technologies.
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Abbott's Data Science & Engineering organization accelerates data-driven solutions and creates business value across the organization related to Artificial Intelligence (AI), Digital Analytics, and Big Data. We use state-of-the-art technologies, build cutting-edge algorithms that solve complex health challenges, and develop reliable, cost-effective tools.
$250,700 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Additionally, the applicant must have employment experience with: (1) Data profiling tools such as Alteryx; (2) Data cataloging tools such as Collibra; (3) Data technology products and components for big data and cloud(AWS, data lakes, and similar); (4) XML and Json file formats; (5) SAS programming skills and use of SAS-pc with data step, macro processing, and procSQL; (6) Software development with object-oriented/object function scripting languages: python, java, JavaScript, C.
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