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Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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Hands-on production experience with orchestration systems such as Airflow. Architect, design, and code shared libraries in Scala and Python that abstract complex business logic to allow consistent functionality across the Data organization.
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Hands-on experience working on analytical platforms like SAS, R, Python, Azure ML. Proficient in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn.
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5+ years hands-on experience with the Big Data stack (HDFS, SPARK, MapReduce, Hadoop, Sqoop, Pig, Hive, Hbase, Flume, Kafka) Hands-on experience with "productionalizing" Big Data applications (e.g. administration, configuration management, monitoring, debugging, and performance tuning.
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Minimum Qualifications: Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, Engineering, or a related fieldAt least 3 years of experience as a Data Scientist, with a focus on developing and deploying machine learning models in production environmentsStrong programming skills in at least one language (Python, SQL, Spark, C.
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Extensive hands-on experience implementing Lakehouse architecture using Databricks Data Engineering platform, SQL Analytics, Delta Lake, and Unity Catalog. Extensive hands-on experience implementing serverless real-time/near real-time architecture using Cloud native services (i.e., Azure, AWS or GCP Tech Stack), and Spark technologies (e.g., Spark Streaming, Spark ML.
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Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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This position is on our Data Enablement Platform team. Invest in building resilient data architectures, participate in on-call rotations and continuously improve our operational efficiency.
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Experience working with cloud environments, including GCP,Cloudrun, OpenShift, Docker/Kubernetes, Data Manipulation, SQL data manipulation (Relational and NoSQL), Products (relational) including SQL Server, Teradata, Oracle, Products (big data) including GCP, Hadoop o Products (streaming) including Kafka and MQTT Build tools o GitHub o Build Tools like Tekton, Jenkins, GRADLE.
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A minimum of six years' experience in providing complex consultative services in the following focus areas: information strategy, big data architecture, information/data governance, master data management, data quality, data integration particularly in a life science or healthcare setting.
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Hands-on development experience with Snowflake features such as Snow SQL; Snow Pipe; Python; Tasks; Streams; Time travel; Zero Copy Cloning; Optimizer; Metadata Manager; data sharing; and stored procedures.
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Proficiency with server-side languages for structured data processing; Python, PySpark, Java, Apache Spark, and SparkSQL preferred. Familiarity with analytical tools for business intelligence and data science such as Power BI, Jupyter, and R Studio preferred.
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As an AI Big Data Engineer, you will focus on creating a Unified Data Platform. Implement data-related business logic on modern data platforms, such as AWS Glue, Databricks, and Azure, using best practices and industry standards.
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Understand and lead the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Experience with "big data" and cloud computing technologies like Redshift, Hadoop, Hive, BigQuery.
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5+ years of experience in test automation and testing integration functions same or like RCSA related business controls Proven hands-on experience in Java, JEE, Streaming, API, Microservices, Containerization and UX/UI tools such as Angular JS/React, etcIn-depth knowledge on data engineering, DB models and architecture in RDBMS, Big Data and other cloud databases such as snowflake, Databricks, etc.
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hands on big data r python jobs in New York, Norwood, Massachusetts
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