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77 West Wacker Dr (35012), United States of America, Chicago, IllinoisLead Data Engineer (python, Spark, Big Data, AWS)Do you love building and pioneering in the technology space.
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Develop and optimize Databricks notebooks for big data processing and analytics in Azure Databricks environments. Expertise in SQL Server Management, Azure Data Factory Development, Databricks Engineering, Delta Parquet File Management, and SQL Server Integration Services.
$169,575 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Build and deploy batch and streaming pipelines to collect and transform our rapidly growing Big Data set within our hybrid cloud architecture utilizing Kubernetes/EKS, Kafka/MSK, and Databricks/Spark.
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Implementation and tuning experience in the Big Data Ecosystem, (such as EMR, Hadoop, Spark, R, Presto, Hive), Database (such as Oracle, MySQL, PostgreSQL, MS SQL Server), NoSQL (such as DynamoDB, HBase, MongoDB, Cassandra, design principles) and Data Warehousing (such as Redshift, Teradata, Vertica, schema design, query tuning and optimization) and data migration and integration.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Strong communication skills and the ability to present complex data in a clear and concise manner, using tools such as Power BI Experience with big data technologies, such as Hadoop or Spark, is a plus Strong problem-solving skills and the ability to work independently or as part of a team.
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Proven experience with big data technologies (e.g., Apache Spark, Apache Flink, Apache Kafka) and cloud-based data platforms (e.g., AWS, Google Cloud, Azure). Strong knowledge of SQL and NoSQL databases, data lake solutions (e.g., Apache Iceberg, Big Query), and ETL processes.
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Lead the design and implementation of scalable, robust, and high-performance data pipelines, ETL processes, and analytics solutions using AWS services, Snowflake, and other Big Data technologies.
$156,000 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Hands-on experience with big data processing frameworks, such as Apache Spark. As a Data Engineer, you will collaborate with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Develop code using Big Data Technologies such as Spark to write MapReduce and in-memory applications using Java, Scala, SQL, Python, R languages, Hive, etc. Previous experience with emerging big data processing technologies (Spark, Kafka, Hive, Hadoop/MapReduce, etc.
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Our client, a premier investment bank, is looking for a Big Data Engineer to join their growing team in Chicago, IL. Currently our client spends a lot of time trying to answer client's questions by logging in to several disparate data sources.
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Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data - HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks.
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Implement and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Snowflake, Talend & Informatica) with cloud/on premise hybrid hosting solutions, on a multi-team/product level.
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Lisa Utzschneider Top 5% of Similar Sized Companies on ComparablyAwardsReviews from current employees Leadership team is extremely transparent in sharing company goals and vision.
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The Big Data Azure Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. 4+ years of experience in traditional and modern Big Data technologies (HDFS, Hadoop, Hive, Pig, Sqoop, Kafka, Apache Spark, hBase, Oozie, No SQL databases.
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big data jobs Title: data engineer in Chicago, CT, Us
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