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Develop strategic partnerships: Foster strong relationships with key partners like Microsoft, Google Cloud, AWS, Snowflake, Databricks, and Informatica. Craft compelling value propositions: Demonstrate how our cloud data services (AWS, GCP, Azure, Snowflake, Databricks) deliver tangible business outcomes and competitive advantage.
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Certification on at least one relevant platform/tool (AWS, Azure, GCP, Snowflake, Databricks, Spark) You will work with tools/platforms like Kafka, Snowflake, and Databricks to help clients get the most out of their data that may be in systems like Salesforce, SAP, SQL Server, or file storage.
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This role demands a strong technology leader with a deep understanding of data engineering technologies and practices, including hands-on experience with leading platforms like Databricks and Snowflake, and a solid grasp of the Azure Databricks platform for scalable data analytics solutions.
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Cloud Platforms: Knowledge of cloud infrastructure and services, preferably Azure, as it relates to Snowflake and Databricks integration. Utilize Snowflake and Databricks for advanced reporting and analytics, providing actionable business insights.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Implement robust security and compliance measures in Azure, Snowflake, and Databricks to protect sensitive data and meet regulatory requirements. Collaborate with business stakeholders and technical teams to understand requirements and design end-to-end solutions that leverage Azure, Snowflake, and Databricks technologies.
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Experience with data warehousing (e.g., Databricks, Snowflake, Redshift, BigQuery, or similar) Experience working in Databricks (including delta live tables, data lakehouse patterns, etc.
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Manage and optimize our data analytics infrastructure (Databricks and Snowflake), including monitoring, troubleshooting, and maintaining high availability. Experience managing Databricks and Snowflake infrastructure.
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You will work with leading edge technologies like Databricks, Azure Data Lake, Azure Data Factory, Snowflake, and more. Knowledge of Data Engineering and the respective tools and technologies (e.g., Apache Spark, Databricks, Python, SQL DB, Data Lake concepts.
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SQL Server, Azure SQL, Azure Synapse, Databricks, or Snowflake. SQL Server, Azure SQL, Azure Synapse, Databricks or Snowflake. Databricks, Snowflake, Python and Data Modelling skills.
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Development experience with cloud-based data warehouse platform (Azure Databricks, Azure Synapse, AWS Redshift, Snowflake, etc.) Designing and implementing performant cloud data warehouse platforms (Redshift, Azure Databricks, SQL DW, Snowflake, or similar.
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Experience with cloud-based data warehousing platforms such as Synapse, AWS Redshift, Google BigQuery, or Snowflake. Mentor and train other data engineers on best practices for data engineering and Databricks usage.
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The candidate will work on building, scaling, and monitoring highly complex BigData platform on Databricks, Snowflake DB and ElasticSearch cloud. Experience as the Databricks account owner, managing workspaces, Unity Catalog, audit logs, and high-level usage monitoring.
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Primary focus on Java application development and enhancements using Java, Python, SQL, Snowflake DB, Databricks spark/Notebook, Azure Blob storage. Familiarity with Databricks and/or Snowflake is a plus.
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Oversee the implementation and use ofdata storage solutions, including PostgreSQL, MS SQL, Amazon RDS/Aurora,Databricks, and Snowflake. Familiarity with CI/CD tools (GitHub,Jenkins, UCD) and data storage solutions (PostgreSQL, MS SQL, AmazonRDS/Aurora, Databricks, Snowflake.
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The Data Management Specialist will be responsible for managing and optimizing our organization's data infrastructure, ensuring data quality, and implementing data solutions using PySpark, DataBricks, Snowflake, and/or Redshift.
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