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SKILLS : Data Engineering, Python, Databricks, Delta Lake, PySpark, AWS, SQL, Machine Learning Operations, Data Analysis. Data Engineer (Python, Databricks, PySpark, AWS, SQL) in O'Fallon, Missouri POSITION : Data Engineer (Python, Databricks, PySpark, AWS, SQL.
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Azure Cloud: Azure SQL Database, Azure Data Lake, Azure Data Factory (ADF), Azure SQL Data Warehouse, Azure Service Bus, Azure analysis service (AAS), Azure Blob storage, Azure Search, Azure App service, Redis cache using pipeline and SSIS, infrastructure as a service(IaaS), Database as a service (DBaaS), Data Migration service (DMS.
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Net (2010 +), Business Objects (Crystal Reports), PL/SQL Developer, Microsoft Excel, Microsoft Visio, and Microsoft Word. Analyze and determine information needs and elements; data relationships and attributes; and data output and reporting capabilities of all applications within the DOI/IA.Provide MS SQL Server, Oracle, and MySQL Database management support services to include both end-user support activities and technical database support activities, such as troubleshooting and configuration.
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Database and data analytics experience is a plus (Postgres, SQL server, Power BI, Tableau, Snowflake, Databricks, etc.) Database and data analytics experience is a plus (Postgres, SQL server, Power BI, Tableau, Snowflake, Databricks, etc.
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Familiarity/experience with various data formats including database specific (Oracle, SQL Server, DB2, Quickbase), text formats(CSV, XML) and Binary(Parquet, AVRO) Hands on experience in Azure cloud services like Azure Data Factory or Azure Synapse, MSSQL Db, Azure SQL DB, Azure Data Lake Storage Gen2, Blob Storage, Python etc.
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Prefer 7 years of experience in data analytics cycle (data gathering, transformation, mining, modeling, analytics, and reporting) using data analytics tools like SAS, Alteryx, Tableau, PowerBI, SQL, R, Python and/or ACL. Strong knowledge and experience with traditional and cloud database technology (e.g. SQL, Snowflake, and/or Azure) and an advanced understanding of data warehousing, data flow and handling.
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Formal AWS training or advanced AWS certifications demonstrating deep knowledge of AWS Compute, AWS Relational database Systems, No Sql databases, Memory processing, server less designs, orchestrations & data streaming (Kafka or Kinesis) is a must.
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Extensive knowledge of and experience with large-scale database technology (e.g. Databricks, Spark, Netezza, Oracle Exadata, Teradata, Greenplum, Google BigQuery, Amazon Redshift, Microsoft Synapse, etc.
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Strong proficiency in Java Stack programming with expertise in the Spring Boot framework, Apache / Tomcat, Apache Maven, Apache Spark, API Concepts and Methodologies, API Security, Camunda, Cloud Automation, Cloud Computing, Cybersecurity, Data Engineering, Database Design (Physical), DevOps, Java and Related Technology, JavaScript, Linux.
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Leveraging experience in database management, migration, and transformation to cloud native DBs like Cloud SQL, Spanner, AWS Aurora, AWS RDS, etc. Designing and developing large scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker and Cloud IAM.
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Database: Oracle, SQL Server, DB2, MySQL, No SQL (Mongo DB) Java (J2SE & J2EE), Python , Servlets, JSP, JSTL, EJB, JDBC, JMS, JNDI, JAXB, JAX-WS, JAX-RPC, Spring/Struts/Hibernate, ElasticSearch.
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Utilize scripting languages like Python, SQL, Ruby and groovy, Container Orchestration services including Docker and ECS, CM tools including Ansible and Terraform, and a variety of AWS tools and services.
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In-depth knowledge of various database management systems (DBMS) such as relational databases (e.g., Oracle, SQL Server, PostgreSQL), NoSQL databases (e.g., MongoDB, Cassandra), and cloud-based data services (e.g., Amazon RDS, Azure SQL Database.
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Expert in SQL, PL/SQL and UNIX shell scripting Conversant with ETLs and basic knowledge of Oracle reports and format Knowledge of underlying the Oracle Applications Technology Stack, database architecture, schemas/products and database objects Experience of upgrading from Oracle Cloud SOA to OIC Knowledgeable about Cloud PaaS and Oracle Analytics Cloud Other Skills: Ability to communicate effectively via multiple channels (verbal, written, etc.
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Azure Synapse Analytics, Azure Databricks, Azure Data Factory, Azure SQL Database, ADLS, Entra (Active Directory), Key Vault, Power BI, and other Azure resource types. Expert level knowledge of SQL, database administration and other data platforms and data related programming elements (e.g., Python.
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