Solution Architect

As a Solution Architect with 7+ years of experience, your role will involve designing, implementing, and optimizing enterprise-scale data platforms with a focus on Databricks. You will be expected to leverage your expertise in big data, cloud-native architectures, and advanced analytics to translate business requirements into scalable solutions while engaging stakeholders effectively. Key Responsibilities: - Architect and deliver end-to-end data solutions using Databricks features like Delta Lake, MLflow, and Unity Catalog. - Design and optimize data pipelines for both batch and real-time processing utilizing technologies such as Spark, Kafka, and Event Hubs. - Collaborate closely with business stakeholders to gather requirements and transform them into technical architectures. - Ensure governance, compliance, and security across data platforms by implementing role-based access and audit controls. - Lead cloud migration projects from legacy systems to Databricks on Azure/AWS/GCP. - Mentor engineering teams on best practices for Databricks, Spark optimization, and cost-efficient cloud usage. - Drive innovation by integrating Databricks with BI tools, machine learning workflows, and enterprise data lakes. Qualifications Required: - Strong hands-on experience with Databricks, including Delta Lake, MLflow, and Unity Catalog. - Proficiency in Apache Spark, Python, SQL, and Scala. - Familiarity with Azure Data Factory, Synapse, Event Hubs, or equivalent AWS/GCP services. - Knowledge of data governance frameworks and cloud security best practices. - Proven track record in designing scalable architectures for large datasets ranging from TBs to PBs. - Ability to optimize performance and reduce costs in cloud environments. - Excellent communication and stakeholder management skills. In addition to the key responsibilities and qualifications mentioned above, if there are any additional details about the company in the job description, please provide them. As a Solution Architect with 7+ years of experience, your role will involve designing, implementing, and optimizing enterprise-scale data platforms with a focus on Databricks. You will be expected to leverage your expertise in big data, cloud-native architectures, and advanced analytics to translate business requirements into scalable solutions while engaging stakeholders effectively. Key Responsibilities: - Architect and deliver end-to-end data solutions using Databricks features like Delta Lake, MLflow, and Unity Catalog. - Design and optimize data pipelines for both batch and real-time processing utilizing technologies such as Spark, Kafka, and Event Hubs. - Collaborate closely with business stakeholders to gather requirements and transform them into technical architectures. - Ensure governance, compliance, and security across data platforms by implementing role-based access and audit controls. - Lead cloud migration projects from legacy systems to Databricks on Azure/AWS/GCP. - Mentor engineering teams on best practices for Databricks, Spark optimization, and cost-efficient cloud usage. - Drive innovation by integrating Databricks with BI tools, machine learning workflows, and enterprise data lakes. Qualifications Required: - Strong hands-on experience with Databricks, including Delta Lake, MLflow, and Unity Catalog. - Proficiency in Apache Spark, Python, SQL, and Scala. - Familiarity with Azure Data Factory, Synapse, Event Hubs, or equivalent AWS/GCP services. - Knowledge of data governance frameworks and cloud security best practices. - Proven track record in designing scalable architectures for large datasets ranging from TBs to PBs. - Ability to optimize performance and reduce costs in cloud environments. - Excellent communication and stakeholder management skills. In addition to the key responsibilities and qualifications mentioned above, if there are any additional details about the company in the job description, please provide them.