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Apache Spark-> Cloudera - CCA Spark and Hadoop Developer (CCA175) Apache Spark-> Databricks Certified Developer: Apache Spark 2. Product SME for Confluent Kafka, Apache Spark, Talend.
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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. Strong hands-on expertise in building Data engineering solutions using Java, Apache Spark and Scala.
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Deep expertise in Performance tuning and optimization of Java/Spark/Scala programs. Data Ingestion to one or more Azure Services - (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks.
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Strong hands-on expertise in building Data engineering solutions using Apache Spark and Scala. Deep expertise in Performance tuning and optimization of Spark/Scala programs. Strong hands-on expertise in building Data engineering solutions using Apache Spark and Scala.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL. 2+ years of experience with Spark. Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL.
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We are seeking a Senior Data Architect with extensive experience in Databricks, Spark, Python, and ETL technologies to join our dynamic team. Leading the architecture and implementation of Spark and Databricks-based ETL frameworks for large-scale enterprise systems.
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Proficiency in utilizing Apache Airflow, Azure Data Factory, and Change Data Capture (CDC) for data orchestration. Utilizing tools such as Apache Airflow, Azure Data Factory, and Change Data Capture (CDC) for orchestrating and managing data workflows.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQLAmazon Web Services (Security Groups, Batch, Lambda, SSH, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis.
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Knowledge of Apache Beam, apache spark, Pubsub or Kafka and IAM. Experience with Airflow/Composer or Tidal to orchestrate the data pipelines. Knowledge of Apache Beam, apache spark, Pubsub or Kafka and IAM.
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Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend. Strong proficiency in programming languages such as Python, Java, or Scala, with expertise in data processing frameworks and libraries (e.g., Spark, Hadoop, SQL, etc.
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Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.) Snowflake or Databricks certifications and/or hands-on-keyboard experience.
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Utilize programming languages like Java, Python, SQL, Node, Go, and Scala, Apache Spark, Apache Splink, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Extensive hands-on experience in building and managing data pipelines using Databricks, Apache Spark, AWS Redshift, and AWS Lake Formation, with a strong emphasis on Spark skills.
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Experience in data platforms such as Apache Spark, Databricks, HD Insight, Experience in data platforms such as Apache Spark, Databricks, HD Insight, PowerBI, Palantir, Python, SQL) to consolidate, cleanse and/or transform and present data from various sources.
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Strong knowledge of data manipulation languages such as Spark, Scala, Impala, Hive SQL, Apache Nifi and Kafka necessary to build and maintain complex queries, streaming and real-time data pipelines.
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