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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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Familiarity with data reporting & affiliate marketing platforms (Tableau, Impact, Snowflake, etc.) Familiarity with data reporting & affiliate marketing platforms (Tableau, Impact, Snowflake, etc.
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Build automation for CI/CD and SaaS delivery on AWS, Snowflake and Databricks. Build automation for CI/CD and SaaS delivery on AWS, Snowflake and Databricks. Configure and maintain systems including but not limited to Kubernetes (EKS and ArgoCD), Kafka, Spark, ElasticSearch/OpenSearch.
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We raised a $300M Series C from Co-Leads D1 Capital Partners and XN, Existing Investors Sutter Hill Ventures and Altimeter Capital, and Snowflake Ventures. Administration of core tech stack outside of CRM such as Outreach, LeanData, data enrichment partners, UserGems, 6sense and others.
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Primary responsibilities will include analysis in our many data sources (Enterprise Data Warehouse, Snowflake, Informatica, MSFT Dynamics, Big Data, Google BigQuery, Adobe Experience Platform) to build recommendation and propensity models as well as working with Data Engineering to identify, clean and integrate data into destination stores.
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At least 2 years of experience with Snowflake, DBT, and/or Fivetran. Snowflake Data Architect. Certification in Snowflake is preferred. At least 2 years of experience with Snowflake, DBT, and/or Fivetran.
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Databricks, Alation, Ab Initio, Talend, AWS S3, Snowflake. Databricks, Alation, Ab Initio, Talend, AWS S3, Snowflake. Solution architect ( Microstrategy Cloud / Business Intelligence / Data Visualization.
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Experience in Big Data integration, including cloud-based platforms such as AWS, and Snowflake. Exposure to training and certification pathways for technical and functional skills from AWS, SnowFlake, Informatica and others.
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
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Improve scalability and performance of the platform through integration with big data frameworks (Databricks, Snowflake, etc. Our patented technology is based on over 11 years of research at the California Institute of Technology and NASA Jet Propulsion Laboratory.
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Experience with big data technologies (e.g., Hadoop, Spark, Databricks, Snowflake) and cloud platforms (e.g., AWS, Azure). Experience with big data technologies (e.g., Hadoop, Spark, Databricks, Snowflake) and cloud platforms (e.g., AWS, Azure.
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Languages and Tools: PL/SQL, Python, T-SQL, StreamSets, Snowflake Streams and Tasks, and Informatica PowerCenter, DBeaver. Database Platforms: Snowflake, Oracle, and SQL Server. Responsible for assisting in configuration and scripting to implement fully automated data pipelines, stored procedures, and functions, and ETL workflows that allow for data to flow from on-premises Oracle databases to Snowflake where the data will be consumable by our end customers.
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Skilled in modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Programming languages: Java, Pyspark, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
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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: 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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Skilled with Python, Git, Containers, CDK, and Terraform, GitLab CI/CD. Your expertise in Python, SageMaker, Spark, CI tools, SQL, Kafka, Kubernetes, and ArgoCD will be the driving force behind setting up fully automated CI/CD pipelines, solving operational challenges, and ensuring the optimal performance of complex systems.
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