CloudIngest is seeking an Azure DataBricks Lead/Architect with AI expertise to design and implement data solutions. This long-term contract role requires strong experience in data architecture, big data technologies, and machine learning frameworks.
## Qualifications - Key Skillset for this Role - Hands-on experience with DataBricks (using Apache Spark, Delta Lake, etc.) - Strong understanding of data architecture and data engineering principles - Solid experience in working with big data technologies such as Hadoop, Spark, Kafka, or similar - Expertise with Snowflake Architecture is a big plus - Experience with AI and Machine Learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) - Experience with cloud platforms (Azure, and AWS, or Google Cloud Platform) and cloud-native data tools - Experience leading or managing teams and projects - Experience with Azure services (e.g., Azure Storage, Azure Synapse, Azure Machine Learning) - Excellent knowledge of data governance and security best practices - Hands-on DevOps best practices and CI/CD pipelines ## Benefits - Job-Type: Long-Term Contract Opportunity - The initial contract is for 12 months, with extensions ## Responsibilities - Work Style: Can work remotely from within North America - Design and architect data solutions using Azure DataBricks - Develop and deploy AI and machine learning models using DataBricks - Integrate DataBricks with other Azure services (e.g., Azure Storage, Azure Synapse) - Optimize data pipelines and workflows for performance and scalability - Collaborate with data scientists and engineers to build AI-powered solutions - Data Architecture Design and Implementation: - Design and implement cloud-based data architectures leveraging DataBricks, Azure, and AWS or Google Cloud Platform - Architect end-to-end data pipelines that integrate with DataBricks and other cloud services - Ensure that the data architecture supports both batch and real-time data processing and analytics - Leverage DataBricks Delta Lake for data storage, management, and processing - Integrate data from various sources, including operational databases, data lakes, and third-party APIs - Work with teams to ensure seamless ETL/ELT processes within the DataBricks environment - Collaborate with data engineers to build data ingestion pipelines and automate data workflows ## Full Description Job-Role/Title: Azure DataBricks Lead/Architect (with AI expertise) Job-Location: Bannockburn, Illinois, United States. Job-Type: Long-Term Contract Opportunity. The initial contract is for 12 months, with extensions. Work Style: Can work remotely from within North America. Key Deliverables: • Design and architect data solutions using Azure DataBricks • Develop and deploy AI and machine learning models using DataBricks • Integrate DataBricks with other Azure services (e.g., Azure Storage, Azure Synapse) • Optimize data pipelines and workflows for performance and scalability • Collaborate with data scientists and engineers to build AI-powered solutions • Data Architecture Design and Implementation: • Design and implement cloud-based data architectures leveraging DataBricks, Azure, and AWS or Google Cloud Platform. • Architect end-to-end data pipelines that integrate with DataBricks and other cloud services. • Ensure that the data architecture supports both batch and real-time data processing and analytics. • Leverage DataBricks Delta Lake for data storage, management, and processing. • Data Integration: • Integrate data from various sources, including operational databases, data lakes, and third-party APIs. • Work with teams to ensure seamless ETL/ELT processes within the DataBricks environment • Collaborate with data engineers to build data ingestion pipelines and automate data workflows. Key Skillset for this Role • Hands-on experience with DataBricks (using Apache Spark, Delta Lake, etc.) • Strong understanding of data architecture and data engineering principles. • Solid experience in working with big data technologies such as Hadoop, Spark, Kafka, or similar. • Expertise with Snowflake Architecture is a big plus. • Experience with AI and Machine Learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) • Experience with cloud platforms (Azure, and AWS, or Google Cloud Platform) and cloud-native data tools • Experience leading or managing teams and projects. • Experience with Azure services (e.g., Azure Storage, Azure Synapse, Azure Machine Learning) • Excellent knowledge of data governance and security best practices • Hands-on DevOps best practices and CI/CD pipelines. We appreciate all the applicants for their interest in working with us, however, only those candidates shortlisted for the next steps in the hiring process will be contacted. Thank you. Cloudingest!
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