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Experience in Data Migration from RDBMS to Redshift/Snowflake cloud data warehouse. Provide direction on adoption of Cloud technologies (Redshift, Postgres, Snowflake,) and industry best practices in the field of data lakes and data warehouse architecture and modelling.
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At least 3 years of experience managing Cloud Data Warehouse database technologies, such as AWS Redshift, Snowflake, Databricks or similar. Design, configure, and manage Data Warehouse Database Systems on Cloud (AWS Redshift, EMR HBase and Snowflake.
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O Database Management System: Storing, organizing, managing, and delivering data using relational DBs, NoSQL DBs, Graph DBs, and data warehouse technologies including AWS Redshift and Snowflake.
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3+ years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Cassandra, MySQL, Snowflake, PostgreSQL, Redshift, Azure SQL Data Warehouse, Databricks, etc.
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6+ years of experience in SQL, data transformations, statistical analysis, and troubleshooting across more than one Database Platform (Cassandra, MySQL, Snowflake, PostgreSQL, Redshift, Azure SQL Data Warehouse, Databricks, etc.
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Experience in optimizing data models and access patterns for modern warehouse and orchestration platforms such as Snowflake, Redshift, Databricks, Spark, DBT, Apache Airflow, and Prefect.
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Developing and maintaining complex ETL mappings, workflows, and UNIX shell scripts in a Data Warehouse environment, based on technical specifications and other supporting documentation, using Informatica PowerCenter, Unix Shell Scripts, advanced SQL, and Autosys/Tidal Enterprise Scheduler, used for data integration.
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The Senior Analytics Engineer is responsible for integrating data into the Enterprise Data Warehouse (EDW) from various internal and SaaS sources using a cloud ELT platform, AWS Lambda/Glue, and Python to support downstream teams with reporting (Snowflake, Databricks or Redshift.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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4+ years using cloud-based warehouse/data lake (Preferably in Azure Databricks metastores/catalogs or similar stacks such as AWS Athena/Redshift, GCP Bigquery, Azure ADLS, etc) Proficiency in building ETL pipelines from API endpoints or data-stores into a cloud data warehouse or lake.
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Familiarity with cloud data storage solutions such as AWS S3, Google Cloud Storage, Azure Blob Storage, AWS Redshift, Google BigQuery, Azure SQL Data Warehouse, or others. Experience with cloud data processing and analytics services such as AWS Glue, Google Dataflow, Apache Spark on cloud platforms, or Azure Data Lake Analytics.
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Familiarity with data modeling, MSSQL and/or Python for ad-hoc analysis, and cloud and native data warehouse systems such as Snowflake, Azure SQL, Redshift, or similar. 5 - 7 years: Hands-on experience with cloud and native data warehouse systems such as Snowflake, Azure SQL, Redshift or similar.
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At least two years experience in implementing, automating and integrating Big Data infrastructure resources like S3, Redshift, Aurora, Kinesis, Kafka, EMR, Lambda, SNS, Azure Blob Storage Account ,SQL Data Warehouse, Microsoft Event Hubs , HDInsights, Azure Databricks, Azure Functions,Event Grid, Data Lake Analytics in an ephemeral/transient and in an elastic manner.
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Extensive hands-on experience working with cloud data warehouse and data lake platforms like Databricks, Redshift or Snowflake. Extensive experience in developing end-to-end orchestration layer for data pipelines using frameworks like Apache Airflow, Prefect, Databricks Workflow.
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Performing data integration using, cloud data integration platforms, tools and languages such as AWS, Redshift, EMR, Python and Object Oriented Programming constructs. Experience: 5 years of technical experience performing ETL development; developing and scheduling batch jobs; developing UNIX Shell Scripts for data validation and reconciliation; designing relational and dimensional databases; performing data integration in AWS using Python and HIVE; developing Python data integration and validation scripts; and performing real-time data integration using messaging queue(MQ.
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Experience working with Data Warehouse technologies (e.g. Redshift, Snowflake) The Data Solution Architect must have familiarity with traditional data technologies (Data Warehouse, Data Lake) as well as transformative capabilities such as Data Lakehouse, Data Fabric, and Data Mesh in order to define go-forward strategies which are compliant for US Govt clients – including addressing Federal Cloud security requirements, data privacy, data security, and data integration approaches which are approved for US Govt use.
$123,000 - $231,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago
redshift data warehouse jobs
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