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77 West Wacker Dr (35012), United States of America, Chicago, IllinoisSenior Manager, Data Engineering (Spark, Scala, SQL) 5+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
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Architect and deploy advanced batch and streaming data pipelines using Kubernetes/EKS, Kafka/MSK, and Databricks/Spark within a dynamic hybrid cloud environment. Hands-on experience with data platforms and technologies like Delta Lake, Spark, Kubernetes, Kafka, ClickHouse, and/or Presto/Trino.
$350,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Deliver best-in-class insights, showcasing our application of data visualization (Power BI, Tableau, Excel) and via analytic tools (R, SAS, JMP, Python, Spark), telling concise, actionable stories.
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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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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. Expert level skills on AWS services, Snowflake, Python, Spark – Certifications are huge plus.
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Architect and implement big data processing solutions using Databricks, leveraging Apache Spark for data transformation, ETL processes, and machine learning workflows. Proficiency in Databricks, Apache Spark, and related big data technologies.
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Design and Implement loosely coupled microservices that are API-driven using Python,Django,and gRPC with protocol buffers, as well as event-driven microservices using Kafka and Apache spark for backend data processing.
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Current projects include development using Scala, Python, Apache Spark, SQL Server, Apache Parquet, Microsoft Azure technologies, and Microsoft Azure DevOps. Join us in our effort to create the highest quality financial research data and providing the input for some of the most influential financial research studies.
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Experience with Big Data frameworks (e.g. Hadoop MapReduce, Spark, Hive, Kafka). Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
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Additionally, they will be working in a technology-driven environment utilizing the latest tools and techniques such as Databricks, Redshift, S3, Lambda, DynamoDB, Spark, and Python. Knowledge of or direct experience with Databricks and/or Spark.
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The Director, Analytics and Insights will be central in driving analytic insights and strategic thinking for a specific Spark Foundry account. Balancing the nimble spirit of a startup with the powerhouse soul of Publicis Media, Spark Foundry delivers the best of both worlds to a client roster that spans some of the world’s best and most beloved brands and companies.
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Expert level skills on ETL tools like Talend and Informatica Expert level skills in Data Warehousing – Modeling, mapping, building batch and real time data pipelines and frameworkExperienced in DataOps tools like GitHub, Jenkins, Udeploy etc.
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Expertise in Databricks, Apache Spark, and big data technologies. Architect and implement big data processing solutions leveraging Apache Spark for ETL, data transformation, and machine learning workflows.
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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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Big Data Tools: Strong experience with big data tools like Apache Spark, Hadoop, and Delta Lake. Certifications: Databricks certifications or cloud certifications (AWS Certified Solutions Architect, Microsoft Azure Solutions Architect Expert, etc.
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spark job in Chicago, IL
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