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Experience with at least 3 of the technologies/tools mentioned here: HAProxy, Kafka, Big Data/ Hadoop, Presto, Spark, Airflow, Pinot, Druid, Opensearch, Gcp, Data Proc. Licensing, Audio, Operating System for TV, Streaming Players and Smart TVs, Smart Home, Streaming Platform, Content Distribution, OTT Advertising, Advertising, Home Entertainment, Streaming Media, and Original Programming.
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Experience with large scale streaming platforms (e.g. Kafka, Event Hub, Databricks Live Table / Structured Streaming), processing frameworks (e.g. Spark, Databricks) and storage engines - stream analytics.
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Experience with large scale streaming platforms (e.g. Kafka, Event Hub, Databricks Live Table / Structured Streaming), processing frameworks (e.g. Spark, Databricks) and storage engines.
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Experience with streaming technologies such as Kafka and Spark. Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks.
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Experience with the Azure Services and Data components: Container based solutions, Microservices, Streaming Solutions, Python & Spark Compute, Spark SQL, Azure Integration services, and ingestion tools such as ADF, Snowflake, ADL, and GenAI Cognitive capabilities.
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Micro-batch streaming and continuous streaming process in Databricks for high latency, low latency and ultra-low latency of data accordingly by using inbuilt Apache spark modules.
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At least 1-2 years building production-grade data solutions (Example: ETL/ELT, Spark, Azure Data Factory, AWS Data Migration Services, streaming systems) Certification on at least one relevant platform/tool (AWS, Azure, GCP, Snowflake, Databricks, Spark.
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Proficiency in Apache Spark, including Spark Core, Spark SQL and Spark Streaming. Apache Spark, Spark Core, Spark SQL, Spark Streaming.
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Experience in architecting data pipelines and solutions for streaming and batch integrations using tools/frameworks like dbt, Talend, Azure Data Factory, Spark, Spark Streaming, etc.
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Expert/Advanced level experience with ETL technologies, Data Streaming using integration patterns like Kafka, Spark Streaming. Experience with Big Data Technologies (NoSQL databases, Hadoop, Hive, Hbase, Pig, Spark, Elasticsearch, Databricks, etc.
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Optimization of Spark jobs and Databricks clusters for better performance. 5+ years Hadoop, YARN, MapReduce, Pig or Hive, Spark. Integration of data from diverse sources, including APIs, databases, streaming data, and external data feeds.
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Hands-on programming experience in Apache Spark using Java/Scala and Spark Streaming. Java - 4, Big data Architect - 3, Spark - 4, ETL - 4 , Apache Beam/DataF. Preferred GCP Data services Experience as requested below, if not should have, strong Hadoop, Java Spark experience or similar data services in AWS.
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In depth expertise with streaming data components Kafka, Spark, Flink Hadoop, Presto/Trino, RedisDemonstrated leadership, mentoring, and collaboration skills balancing strategic and tactical needs.
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Design, Implement and maintain Data platforms, Compute services using Databricks, Azure Functions, Service Bus, Container Apps and SPARK computing etc. As a Senior Director, your key responsibilities include: Data Strategy, Data Engineering, Cloud data platforms, Master Data Management, and Data Management.
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Experience with building stream-processing systems, using solutions such as Kafka, Storm or Spark-Streaming. Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark.
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