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Hadoop/Big Data/Databricks Certifications. Performance tuning in Big Data environments, Spark, ADF, Snowflake. Understanding of Big Data technologies such as Spark, NiFi, Impala, Sqoop, Hive, and File formats like Parquet, AVRO, ORC, CSV, JSON.
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Title: Lead Data Engineer – Big Data. Be in tune with emerging trends Big data and cloud technologies and participate in evaluation of new technologies. Provide technical expertise in the areas of design and implementation of Ratings Data Ingestion pipelines with modern AWS cloud and other technologies such as S3, Hive, Databricks, Scala, Python and Spark.
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3+ years experience with Big Data technologies, such asApache Hadoop, Hive or Spark, Databricks and/or Snowflake. The ideal candidate will lead the architecture and implementation of on-premises and cloud big data solutions as part of enterprise data modernization.
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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Utilize Databricks for big data processing and streaming analytics. Experience with big data technologies, such as Apache Hadoop, Spark, Kafka, and others. Stay current with emerging trends and technologies in cloud computing, big data, and data engineering.
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As a big data engineer at Booz Allen, you'll implement data engineering activities on some of the most mission-driven projects in the industry. We need an experienced data engineer like you to help our clients find answers in their big data to impact important missions-from fraud detection to cancer research to national intelligence.
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Experience in implementing machine learning algorithms in big data environments. Experience in building and optimizing big data pipelines, architectures, and data sets.
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Experience of implementing Amazon EMR or Big Data technologies like Hadoop, Spark, Presto, Hive will be a plus. Implementation experience of Big Data technologies like Hadoop, Spark, Presto, Hive, and Hue will be a major advantage.
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Leverage AWS cloud services like S3, Redshift, EMR, Glue, Lambda, and others in combination with Data Lakehouse platform/Apache Spark Integration for advanced data processing and analytics.
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This position requires a blend of skills in cloud computing, data engineering, and analytics. Ensure high standards of data quality and implement data governance practices. BS in Computer Science, IT, Software or Computer Engineering, Data Science or Analytics, Mathematics or related field.
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Develop and maintain data lakes and data warehouses on AWS and Data Lakehouse Platform, ensuring data integrity and accessibility. The Cloud Data Engineer plays a crucial role in designing, implementing, and managing advanced data solutions using both AWS and Data Lakehouse platforms.
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Familiarity with ETL tools, processes, and data integration techniques. 3-5 years of data engineering experience. Automate data workflows and ensure high data quality and reliability.
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Cloud Data Engineer. Understanding of data modeling, data warehousing, and data lake concepts. Provide ongoing support for the platform, troubleshoot any issues that arise, and ensure high availability and reliability of data infrastructure.
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Experience in designing, building, and maintaining data warehouses. Design and implement scalable and efficient data pipelines using AWS and Data Lakehouse Platform services. Optimize data storage and processing for performance and cost efficiency.
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Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing,accessing, and transforming data in a variety of relational databases.
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big data jobs Company: Eagle Home Care
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