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Experience with data technologies: Hadoop, Spark, Kafka, Spark & Kafka Streaming, Python, Scala, Talend etc. AWS Cloud Practitioner or more advanced AWS certification preferred. Experience with modern data architectures and modern data platforms like Snowflake, Databricks etc.
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Collaborates in implementing components of data strategy – Master Data Management (MDM), data virtualization etc. In the process, the role will have the opportunity to act as a Data Advisory member for the Actuarial, Business Intelligence (BI), Data Science, and Data Engineering teams, as well as a collaborator and contributor to Enterprise Data Architecture.
$113,668 - $203,468 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Sr. Data Engineer will join a Data Engineering Team focused on data architecture and development in an AWS / Snowflake environment. REQUIREMENTS: Data Engineering in a AWS / Snowflake environment.
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Create and optimize ETL processes using tools like SSIS, Informatica, Talend. Proficiency in cloud technologies such as AWS, Azure, and GCP, with experience in Databricks, BigQuery, and other cloud-based services.
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Knowledge and/or experience working with Apache Spark/Databricks. We are hiring talented Senior Data Engineers in roles related to building cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development.
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On-site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes. Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks.
$110,000 - $199,000 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep experience and knowledge with Google Cloud Platform, Cloud Dataflow, Airflow, GKE, Pub/Sub, BigQuery, vertex AI, and Dataproc/Spark. Significant experience working with Python, Spark, SQL, Bash, BigQuery.
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Good knowledge in Querying and analyzing large amount of data on Hadoop HDFS using Hive and Spark Streaming and working on systems like HDFS, YARN, Hive, HBase. Spark, Kafka, RabbitMQ, Impala, Kudu, Redis, Hue, Tableau, Grafana, MariaDB, and Prometheus.
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Proficient in programming languages and tools (Python, R, SQL, NoSQL, Spark). Proficient in programming languages and tools (Python, R, SQL, NoSQL, Spark). This role demands a blend of expertise in data science and a deep understanding of the semiconductor industry, aiming to harness advanced data analytics, predictive modeling, and artificial intelligence to address complex business challenges.
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Net, C#, Android SDK, Kotlin, IOS Swift, AWS: EMR, S3, Redshift, Athena, Glue, DynamoDB, Lamda, CloudWatch, ElastiCache, Kinesis, SNS, SQS, Azure: HDInsight, Data Factory, Data Lake Analytics, Databricks, GCP, and Big Data Apache: Hadoop, Hive, Hue, Sqoop, Kafka, Spark, Airflow, SnowFlake, Python, Scala, Machine Learning: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Apache Mahout, Vertex AI, Keras, OpenNN, Theano.
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Other Tools and connectors - Ops/Cloud Manager, Compass, Connector for BI, Connector for Spark. Other Tools and connectors - Ops/Cloud Manager, Compass, Connector for BI, Connector for Spark. Government experience is highly preferred, SLED, Civilian, Military, etc.
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Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA. Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA.
$58,300 - $133,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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3+ years’ experience with analytics platforms and tools, such as Databricks, Snowflake, Teradata, Spark, Kafka. 3+ years’ experience with analytics platforms and tools, such as Databricks, Snowflake, Teradata, Spark, Kafka.
$100,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Extensive experience developing solutions using Spark/PySpark, Scala, Python, and AWS services such as Lambda, Redshift, Glue, Oracle RDS and S3. Strong AWS hands-on experience in data warehousing using services like Glue, Lambda, Redshift, S3, Python, Scala, and Spark.
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Hands-on experience with big data application development and/or with cloud data warehousing (e.g. Spark, Redshift, Snowflake, Azure SQL DW, BigQuery) Hands-on experience with big data application development and/or with cloud data warehousing (e.g. Spark, Redshift, Snowflake, Azure SQL DW, BigQuery.
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