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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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Understanding of database platforms (On-Prem & Cloud-based): SQL Server, MySQL, AWS Redshift, Google PostgreSQL, Oracle. Experience with healthcare terminology concept codes (SNOMED, ICD-10, LOINC, etc.
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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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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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5+ years of experience with SQL or NoSQL database (PostgreSQL, MySQL, SQL server, Oracle, Aurora, Presto, BigQuery) Experience cloud-based data warehousing and data lake solutions like Snowflake, Redshift, Databricks.
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Experience working with Cloud Data Warehouses/Platforms, especially Snowflake, Redshift, Databricks, and BigQuery. Expertise in one or more of the following RDBMSes: PostgreSQL, MySQL, Oracle, SQL Server.
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You will be hands-on with PostgreSQL, Redshift, Kubernetes, and other AWS technologies and you will be working within a team that builds, designs, and supports cloud based ETL, containerized solutions and data warehouses that enable data reporting, analytics, and data science.
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Advanced level proficiency with at least one ETL / Data Orchestration technology (Azure Data Factory, SSIS, Informatica, Alteryx, Ab Initio, Pentaho, Talend, Matillion) Fringe –A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them – ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more.
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Extensive knowledge of PostgreSQL, related AWS services (RDS/PG, Aurora, and Redshift), and associated tools. Maintain and enhance the functionality and performance of existing PostgreSQL-based database systems, including PostgreSQL running in WSL Docker and AWS RDS/PG.
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4 years of experience in working with high-scale or distributed RDBMS and/or NoSQL platforms (e.g. PostgreSQL, Redshift, BigQuery, Couchbase, MongoDB, Cassandra, HBase, Neo4J etc. 4 years of experience in working with high-scale or distributed RDBMS and/or NoSQL platforms (e.g. PostgreSQL, Redshift, BigQuery, Couchbase, MongoDB, Cassandra, HBase, Neo4J etc.
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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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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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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.
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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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Data Processing Frameworks: Lead the implementation and optimization of 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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