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Previous biotech/ pharma experience Master Data Management and Governance Big Data, Data Analytics TOGAF, Architectural frameworks (TOGAF is an architectural framework like ZACHMAN, UAM, others.
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Job Schedulers – Airflow, Oozie or other ETL Scheduler Data Analytics – AWS Cloud Native Services Big data architecture – Python, Scala, Hadoop Bigdata, Hive, Pyspark etc. Data bases (SQL, NoSQL) and Data Platforms (Databricks, Snowflake) Strong skills with Database management, Data modeling and design DevOps and Security CI/CD, Serverless compute, OAuth, SSO, MFA etc.
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Significant experience with cloud platforms (AWS) and building data pipelines Expertise in distributed systems, microservices, and big data technologies (e.g., Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, PySpark.
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We are looking to speak to Big Data Architects or developers, or in fact, anyone who has legitimately been through 1 full life cycle using any Cloudera product to drive Big Data Strategies in an organization.
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We utilize a plethora of open source and industry accepted technologies for our big data problems such as Apache Spark, Apache Storm, Amazon Web services, and Apache Kafka. Collaborates with other peer organizations (e.g., Business Analyst, Data Modeler, QA, SRE, technical support, etc.
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Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark. Enable functionality to support analysis, model optimization, statistical testing, model versioning, deployment and monitoring of model and data.
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Understanding of foundations of Big Data systems and hands-on experience with distributed computational frameworks such as Apache Spark / Apache Beam and NoSQL data stores. Experience with working on large data sets, especially with Spark, Python and Java. Experience with cloud computing platforms, such as AWS or GCP. Experience with Kubernetes.
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Debugs and troubleshoots problems in data flow, lineage, transformation and other stages of the ETL pipelines. Has worked with partner data scientist, data analysts and other domain experts to understand their needs and be able to develop solutions.
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Our capabilities range from C5ISR, AI and Big Data, cyber operations and synthetic training environments to fleet sustainment, environmental remediation and the largest family of unmanned underwater vehicles in every class.
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A fast-growing company with plenty of opportunity for personal growth and development A hard technical challenge to solve with exciting modern technology - cloud computing, Big Data, DevOps, machine learning The ProcessApply now with your CV and any supporting information.
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Demonstrating relevant project management experience in organizing and leading teams including Big data engineering (Hadoop, Spark, Scala, Kafka) and ETL pipeline development (tools: IICS/AWS Glue/SAP BODS/ SSIS/SnapLogic); preferable in P&C Insurance data warehouse.
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Center 3 (19075), United States of America, McLean, VirginiaPrincipal Data Scientist - NLPAt Capital One, we think big and do big things. Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics.
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From special interest would be relevant expertise for: o Digital Twin-enabled Energy Efficiency on the shopfloor o Computer Vision based Quality Inspection • Knowledge of the digital and industry 4.0 technologies that can enhance the shopfloor or operations performance, such as IoT, cloud computing, big data analytics, artificial intelligence, robotics, additive manufacturing, etc.
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It is changing the way Healthcare Marketing is done by leveraging latest cloud-native solutions, efficient big data pipelines, processes and technologies. This individual will work directly with the Data Architect, along with the CTO of Lasso to establish a Machine Learning platform along with best practice engineering standards to ensure secure and successful data solutions.
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Our interdisciplinary team uses expertise in medicine, software, Big Data, machine learning, public health and mathematics to transform records from a diverse set of sources into enriched, research grade data which allows us to generate unique insights in a variety of disease areas.
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