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Required Skills: MS SQL Server MariaDB SolarWinds DPA Index Tuning E-R Diagramming Data Normalization Backup and Restore Clustered Databases Query Optimization MongoDB PostgreSQL Database Tools: SQL Server Management Studio, Azure Data Studio, SQL Profiler, SQL Prompt.
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We implement modern backend solutions that support microservices architecture with the following technologies: NET Core, Node.js, Java, SQL Server, PostgreSQL, MongoDB, Redis, RabbitMQ. For the web UI front-end development, we opt for React, or Angular, and for mobile development — Swift, Kotlin, Java. Most of the systems are designed for cloud infrastructures like AWS, Azure, GCP, and heavily rely on Docker, Kubernetes while modern CI/CD is made using GitLab CI or TeamCity.
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Experience with large scale enterprise applications using big data open-source solutions such as Spark, Kafka, Elastic Search / Solr and Hadoop, HBase- Experience or knowledge of basic programming and DB's technologies (SQL, Python, Cassandra, PostgreSQL, AWS Aurora, AWS RDS , MongoDB, Redis, Couchbase, Oracle, MySQL, Teradata.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Hands-on development experience with Relational DBs (MS SQL Server, PostgreSQL, Oracle), as well as complex stored procedures and functions using SQL and optimization of SSIS packages and Redshift database queries.
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Comprehensive knowledge of database storage systems, encompassing relational databases (SQL-Server, PostgreSQL, Oracle etc), NoSQL databases (Cassandra, MongoDB etc.) Big Data Analytical Platforms: Experience with big data technologies like Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc.
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As a Senior Data Engineer on the MMA National IT Data and Analytics Team, we will count on you to develop and maintain scalable data pipelines, enhance data models, and provide subject matter expertise in data acquisition and consumption pipelines on Azure, Databricks and Confluent.
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Solid understanding of DevSecOps, Git integration, Code deployment using CI/CD pipelines, managing work in an agile environment using Azure Boards, Confluence. Experience designing and building data pipelines using APIs, BigQuery and Streaming ingestion methods.
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You will be responsible for managing a team of DBA's to maintain Relational databases that include Oracle, Sybase, mssql server, AWS RDS, PostgreSQL. The DBA manager will be providing database advisory and consulting services for the enterprise.
$150,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Database Server on premise and AWS cloud skills are a must with Oracle and PostgreSQL. The basic automation skills, such as Ansible, Python, terraform for IAC are required. Database Server on premise and AWS cloud skills are a must with Oracle and PostgreSQL. The basic automation skills, such as Ansible, Python, terraform for IAC are required.
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Working knowledge of databases, such as MongoDB, Oracle, SQL Server, PostgreSQL. SQL, SQL Server, PostgreSQL, Oracle, RDBMS. A Python developer is responsible for writing server-side web application logic using Python frameworks, such as Django, Flask, or ArcGIS GeoProcessing Services.
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Skills Preferred:Extensive expertise in one or multiple database management systems (DBMS) such as Oracle, Microsoft SQL Server, MySQL, PostgreSQL, or MongoDB, encompassing tasks such as installation, configuration, maintenance, and troubleshooting of these systems.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Learn more about what makes us different and how you can thrive as a Senior Data Engineer at MMA National. Knowledge in Azure IoT, Azure HDInsight + Spark, Kafka and Azure Stream Analytics is a bonus.
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These may include but are not limited to: Tools: Boundless Spatial suite, Remote View, PostgreSQL, and/or other geospatial databases, QGIS, ArcGIS Desktop, ArcGIS Server, Image Server, and File Geodatabases.
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Experience in databases (Oracle, SQL Server, PostgreSQL, etc.) data movement (real-time replication or ETL/ELT), multiple clouds (AWS, Azure Google, Alibaba), cloud analytics destinations (Snowflake, Databricks, Kafka, RDS, Synapse, BigQuery, etc.
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It involves developing best practices, reusable code, libraries, and frameworks for cloud-based data warehousing and ETL, and uses multi-cloud, programming languages like Java, Scala, Python, RDBMS, NoSQL databases, and design enterprise data warehouse platforms.
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