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We are expanding our Data Engineering toolset and need an experienced AWS, Python and SQL Data Engineer. As a Data Engineer on our Data Engineering team, you will also design, write, scale, and maintain complex data pipelines using Python within our development framework.
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The ideal candidate will have a strong background in data engineering, with specific expertise in Power BI, SQL, Python, and Databricks. Proficiency in Databricks, with hands-on experience in developing data models and working with notebooks in SQL and Python.
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Proficiency in Python, Scala, or SQL for data manipulation in DataBricks. We're hiring a skilled DataBricks Implementation Specialist to design, deploy, and manage DataBricks environments for optimal data processing.
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Role name: Analyst Role Description: Job Duties:§ Perform hands-on validations and reviews, write quality reports, data strategy, including data governance and data quality to empower the Financial Risk Management (FRM) area.
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Experience to include working on Azure Data Factory (ADF), Oracle, SQL server, Azure Databricks, Azure Synapse Analytics, Data Lake Storage, Azure PaaS services, SSIS packages, Azure Cosmos DB (SQL API), Python, Spark applications, Azure SQL, SQL queries, Azure Monitor and Alert services, GIT Support, ARM Templates.
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Total 10+ years of experience with 3 plus years of experience in data engineering/ETL ecosystems with Palantir Foundry , Python , PySpark and Java. Our client is looking for an PALANTIR - Senior Data Engineer with a Long-Term Contract in Dallas, TX (Onsite) below is the detailed requirement.
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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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Knowledge of Data Streaming products such as Kafka, Confluent Platform, Azure Eventhub, Azure Streaming Analytics, Azure Data Factory, Azure Synapse, Databricks, Google BigQuery and Google PubSub, SAP Data Intelligence and SAP DataSphere.
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Technical Skills: Proficiency in SQL, database platforms (e.g., MySQL, Oracle, SQL Server), data warehousing, ETL processes, data modeling tools, and familiarity with cloud services (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data pipeline tools (Apache Kafka, NiFi.
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Strong skills in Big Data technologies (Hadoop, Spark, Hive) and AWS services (S3, EMR, Lambda, Redshift, CloudFormation). Proficiency in Python, Java, Pyspark, Airflow, and familiarity with real-time data streaming technologies.
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6 years of experience must include: Ab initio, Informatica, Data Stage; Teradata, IBM DB2, Cognos, Oracle PL SQL; Autosys, Control-M, Erwin, XML, HTML, CSS, Unix Shell Scripts; Data Analysis, Data Processing, Code Optimization, Performance tuning; Automating Business Process and Models; Microsoft Visio, Web Services, Crystal Reports; and HP Quality Center, ALM, VSS, EME, XSD. At least 3 years must include: Hadoop, HDFS, Big Data, Hive, Spark.
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Job Title : Data Engineer (Palantir) Any knowledge of the Palantir Foundry Platform will be a big plus. Hands-on experience in Palantir & PySpark to build data pipes in AWS environments.
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Big data technologies/services expertise (Delta Lake, Lakehouse, Medallion, Spark, Python, Kinesis, S3, Glue, EMR, Airflow, Step Functions, Redshift, Athena, Lambda, ML) AWS preferred.
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F5 certifications like BIG-IP Certified Professional (ACP) or BIG-IP Certified Specialist (BCS). Your expertise will span across data center operations, web hosting support, general server administration, and network security.
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The ideal candidate will have a strong background in data engineering, using Azure, Snowflake and/or Databricks, and Python to create data pipelines, integrate diverse datasets, and deliver actionable insights.
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big data python r jobs Title: engineer in Dallas, TX
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