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Proficiency in data storage technologies such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Snowflake, Redshift), and data lakes (e.g., Amazon S3, Azure Data Lake Storage.
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Some of the technologies we use include PostgreSQL, MySQL, Redshift, S3, Meltano, Airflow, Python, and Kubernetes. Strong understanding of OLAP database design and proficiency utilizing a database such as Redshift or Snowflake.
Full-timeRemoteExpandApply NowActive JobUpdated 13 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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Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Data Processing Frameworks: Implement and optimize data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
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Our back-end needs to be scalable, robust, and secure to handle large amounts of event data and analytical processing on the modern data stack (Snowflake/BigQuery/Redshift, Airflow etc. Proficiency in at least one of the SQL languages ( MySQL , PostgreSQL , SqlServer , Oracle.
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Expertise with OLTP (i.e. MS SQL Server, Oracle, MySQL, PostgreSQL) and OLAP (i.e. Redshift, Snowflake, BigQuery, Synapse) database technologies. Expertise with OLTP (i.e. MS SQL Server, Oracle, MySQL, PostgreSQL) and OLAP (i.e. Redshift, Snowflake, BigQuery, Synapse) database technologies.
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This position will be responsible for the implementation, maintenance, development, and performance of critical databases with primary focus on Microsoft SQL Server, Azure, Amazon Redshift, MySQL, PostgreSQL, and Amazon RDS. The qualified candidate will display excellent problem solving, analytical, communication, coordination and task management skills.
Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Expertise in data storage technologies such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Snowflake, Redshift), and data lakes (e.g., Amazon S3, Azure Data Lake Storage.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS Glue, Azure Data Factory, or Google Dataflow. 5+ years of experience in data engineering or systems engineering, with a focus on data systems technologies.
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3 years of AWS Cloud database experience (Redshift, RDS/Postgresql, S3). This is an exciting opportunity to be part of the Puyenpa team supporting the Department of Homeland Security DAC-TER Customs Border Protection program.
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Additional Cloud Data warehousing experience with Snowflake, Azure Data, Redshift and other. Strong Database experience with Oracle, SQL Server, MySQL, PostgreSQL and other. working with deployment and data pipeline technologies such as Airflow, dbt, etc.
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Learn more about what makes us different and how you can thrive as a Power BI Developer at MMA. As a Senior Data Engineer on the MMA 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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Strong skills in languages such as Python, R, SQL or Scala, alongside experience of using modern and traditional data technologies including: ElasticSearch, MongoDB, PostgreSQL, mySQL/mariaDB, Oracle, SQL Server, Hadoop, Kafka, Splunk/ELK or other logging and monitoring tools, BI and Data Warehousing solutions and ETL and migration technologies.
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Proficiency in SQL and experience with database management systems (e.g., MySQL, PostgreSQL, MongoDB, Redshift, Snowflake). Experience with Salesforce, AWS Redshift, Snowflake, Informatica, Tableau, MuleSoft.
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Understanding of DevOps and AWS. Desired: Experience with other technologies used including Docker, AWS, NIFI, Jenkins, Hibernate, Oracle and PostgreSQL Database along with Redshift and Dynamo DB. Experience with Apache Spark and Kafka is a big plus.
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