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You must be passionate about data engineering, possess a solid background in Azure and Databricks, and thrive in a collaborative and innovative environment. Minimum of 5 years of experience in data engineering roles, with a focus on Azure and Databricks.
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The Databricks Engineer will serve as a central figure in our data engineering team, delivering highly sophisticated technological solutions using Databricks, Delta Live Tables, Snowflake, and Medallion Architecture.
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Inviting applications for the role of Assistant Vice President - Global Databricks and Snowflake Alliances. The primary role of the Databricks and Snowflake Alliances Leader is to work with the Global Head of Data and AI Alliances Leader and manage strategic and tactical initiatives established between Genpact and Databricks and Snowflake.
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Must have: SQL, Python, Splunk, Kubernetes, Azure Devops, Power Bi, Git, Airflow, Delta Lake storage databricks platform, Spark (PySpark, Spark SQL) Technologies - IaaS (AWS or Azure or GCP), Databricks platform, Delta Lake storage, Spark (PySpark, Spark SQL.
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Minimum of 4+ years of experience in data engineering, focusing on DataBricks and/or Snowflake. Technical Expertise: Utilize expertise in DataBricks and Snowflake to design and implement scalable, reliable, and efficient data solutions.
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Experience with native and third-party Databricks integrations (Delta Live Tables, Auto Loader, Databricks Workflows / Apache Airflow, Unity Catalog). Design and build data solutions using Databricks, SQL, Python, Spark, and Delta Lake in the Azure ecosystem (Blob Storage, Data Factory, Event Hubs.
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Utilize Databricks for big data processing, analytics, and machine learning workflows. Optimize data processing and query performance for large-scale datasets within Azure and Databricks environments.
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Experience in Databricks workspaces, Databricks notebooks, Job clusters, Delta Lake, Databricks Lakehouse and Unity catalog. Design, Implement and maintain Data platforms, Compute services using Databricks, Azure Functions, Service Bus, Container Apps and SPARK computing etc.
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Responsible for the administration, configuration, and optimization of the Databricks platform to enable data analytics, machine learning, and data engineering activities within the organization.
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Distributed Data Engineering, PySpark, Python, Hadoop, Databricks, Scala. Distributed Data Engineering,PySpark,Python,Hadoop,Databricks,Scala. Minimum of 5 years of hands-on data engineering experience using distributed computing approaches (Spark, Map Reduce, DataBricks) Proven track record of successfully designing and implementing cloud-based data solutions in Azure Deep understanding of data modeling concepts and techniques.
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Must have : SQL, Snowflake, ADF, Databricks, Python, Tidal scheduling. Experience building data piplines using Azure Data Factory and Databricks (good to have) Knowledge of Azure/Databricks/Python is a plus (good to have.
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Building ETL processes using metadata driven frameworks based on ADF/Databricks. Designing and developing Azure-based data solutions using Azure Data Factory, Azure Databricks, Azure SQL Database, and Azure Synapse Analytics.
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Utilize Spark, Databricks, Tensorflow, and Python to handle data extraction, analysis, and model development. Proficiency in Python development, Tensorflow, and Databricks. Utilize Spark, Databricks, Tensorflow, and Python to handle data extraction, analysis, and model development.
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Proficiency with Azure, Databricks, Azure Data Factory, SQL, Python, and Snowflake. The successful candidate must have a strong technical background and ability to work with SQL, Python, Azure Data Factory, Databricks, and Snowflake.
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Serve as system admin to manage AWS and Databricks platform. Experience with ETL tool, for example Databricks. Hands-on development experience with Databricks. Experience on AWS, familiar with EC2, S3, Redshift/Spectrum, Glue, Athena, RDS, Lambda, and API gateway.
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databricks job
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