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As an integral part of our team, you will not only need to tackle operational challenges at every layer of the system infrastructure, but also set up essential tools like Spark, Databricks, Snowflake, Kubernetes, and Kafka for data science infrastructure.
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Experience with Oracle, Spark, Hadoop, Athena, API, FastAPI, Flask, ReST. Python, Spark, Hadoop, and Docker with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design.
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Required Skills: Extensive working experience with HDFS, Spark, Spark Streaming, Oozie, Hive, Kafka, Kafka Message Queues, Splunk, Flume, Pig, Scala, and Sqoop. Key Required Skills: Extensive experience in Design, implementation; support data ingestion, and consumption pipelines for enterprise-scale datasets using Big Data tools, such as Kafka, Spark, Oozie, Hive, MapReduce, Flume, Pig, Scala, Python, and Java Requirements Basic Qualifications: Bachelors Degree in Computer Science, Mathematics, Engineering or a related field with 7+ years of experience.
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Configure and maintain systems such as Kubernetes (Helm, Charts, ArgoCD), Kafka, Spark, Elastic, Bitbucket / GitLab, Nexus, and Jenkins. Radian is helping to ensure the American dream of homeownership in even bigger and better ways with industry-leading mortgage insurance and a comprehensive suite of mortgage, risk, real estate, and title services.
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Data Management: Primary Skills: PIG, Py-Spark Secondary Skills: NiFi, PressureWave. API: Required: Python, Django or Flask, Database experience using MongoDB or MariaDB, ReST endpoint development, Micro service model Desired: Swagger, AWS, C2S or other cloud experience, Docker, Visual Studio Code or similar IDEs, JSON and/or XML serialization, Jira, Confluence, Git version control, Experience working in Agile environment.
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3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) West Creek 3 (12073), United States of America, Richmond, VirginiaSenior Data Engineer (Python, Scala, or Spark)Do you love building and pioneering in the technology space.
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Perform other duties as assignedQualifications and Education Requirements:Degree in Information Systems, Computer Science, Engineering, or related field, or the equivalent combination of education, training, and experienceWorking knowledge of message-oriented middleware/streaming data technologies such as Kafka, MQ, Azure Event Hub, Spark, Spark StreamingMust have strong programming skills / experience in C.
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At least 2 years of working with data platforms and systems (Elastic, Splunk, Azure Data Factory, Apache Spark, Snowflake, Databricks, SQL databases, etc.) At least 2 years of working with data platforms and systems (Elastic, Splunk, Azure Data Factory, Apache Spark, Snowflake, Databricks, SQL databases, etc.
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Experience with automated delivery pipelines, agile delivery and test-driven developmentIn-depth experience with server-side frameworks such as Spring Boot and TomcatIn-depth knowledge of software design patternsIn-depth RDBMS development experience (e.g. SQL Server, PostgreSQL, MySQL)Solid understanding of Spark, Redshift, Apache Ni-Fi helpfulSolid understanding of cloud native architectures (AWS, etc.
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Experienced with general programing, statistical languages, and deep learning packages used to manipulate data and build statistical and machine learning models at a large-scale, such as Python, Spark, PyTorch, Tensorflow, Keras, SQL, and SQL-like query languages for NoSQL databases.
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3 years of technical expertise in any of the following: SQL, Python, Databricks, Azure Data Factory/Synapse and Apache Spark. 3 years of technical expertise in any of the following: SQL, Python, Databricks, Azure Data Factory/Synapse and Apache Spark.
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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 2+ years of data warehousing experience (Redshift or Snowflake.
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Technologies such as Hadoop, Hive, Pig, Spark. OLAP (RedShift, Presto, Snowflake) or non-relational (MongoDB, DynamoDB) database technologies. Amazon Web Services (AWS) technologies, Microsoft Azure or Google Cloud Platform will be strongly considered.
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Streaming Data Pipelines: Develop and maintain real-time data streaming pipelines using technologies such as Apache Kafka, Apache Flink, or Apache Spark Streaming, ensuring low-latency and high-throughput data processing.
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Work with a state-of-the-art data technology stack (Spark, Tensorflow, Pytorch, Snowflake, Airflow, AWS Ecosystem) that operates in the cloud to empower predictive modeling services for both internal and external customers.
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spark job in Baltimore, MD
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