MLOps Architect (Databricks Specialist)
Job Description:
• 12+ years in IT experience with a minimum 10+ Years of experience in data engineering, data platform, and analytics.
• Projects delivered with hands-on experience in development on Databricks.
• Working knowledge of any one cloud platform (AWS, Azure, or GCP).
• Deep experience with distributed computing with Spark, including knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps.
• Current knowledge across the breadths of Databricks product and platform features.
• Familiarity with optimization for performance and scalability.
• Completed data engineering professional certification and required classes.
• Minimum qualifications:
• Educational Background: Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience).
Technical Skills:
• Expert-level proficiency in Spark Scala, Python, and PySpark.
• In-depth knowledge of data architecture, including Spark Streaming, Spark Core, Spark SQL, and data modeling.
• Hands-on experience with various data management technologies and tools, such as Kafka, StreamSets, and MapReduce.
• Proficient in using advanced analytics and machine learning frameworks, including Apache Spark MLlib, TensorFlow, and PyTorch, to drive data insights and solutions.
• Databricks Specific Skills:
• Extensive experience in data migration from on-premises to cloud environments and in implementing data solutions on Databricks across cloud platforms (AWS, Azure, GCP).
• Skilled in designing and executing end-to-end data engineering solutions using Databricks, focusing on large-scale data processing and integration.
• Proven hands-on experience with Databricks administration and operations, including notebooks, clusters, jobs, and data pipelines.
• Experience integrating Databricks with other data tools and platforms to enhance overall data management and analytics capabilities.
Certifications:
• Certification in Databricks Engineering (Professional)
• Microsoft Certified: Azure Data Engineer Associate
• GCP Certified: Professional Google Cloud Certified.
• AWS Certified Solutions Architect Professional
Job Description:
• 12+ years in IT experience with a minimum 10+ Years of experience in data engineering, data platform, and analytics.
• Projects delivered with hands-on experience in development on Databricks.
• Working knowledge of any one cloud platform (AWS, Azure, or GCP).
• Deep experience with distributed computing with Spark, including knowledge of Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps.
• Current knowledge across the breadths of Databricks product and platform features.
• Familiarity with optimization for performance and scalability.
• Completed data engineering professional certification and required classes.
• Minimum qualifications:
• Educational Background: Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience).
Technical Skills:
• Expert-level proficiency in Spark Scala, Python, and PySpark.
• In-depth knowledge of data architecture, including Spark Streaming, Spark Core, Spark SQL, and data modeling.
• Hands-on experience with various data management technologies and tools, such as Kafka, StreamSets, and MapReduce.
• Proficient in using advanced analytics and machine learning frameworks, including Apache Spark MLlib, TensorFlow, and PyTorch, to drive data insights and solutions.
• Databricks Specific Skills:
• Extensive experience in data migration from on-premises to cloud environments and in implementing data solutions on Databricks across cloud platforms (AWS, Azure, GCP).
• Skilled in designing and executing end-to-end data engineering solutions using Databricks, focusing on large-scale data processing and integration.
• Proven hands-on experience with Databricks administration and operations, including notebooks, clusters, jobs, and data pipelines.
• Experience integrating Databricks with other data tools and platforms to enhance overall data management and analytics capabilities.
Certifications:
• Certification in Databricks Engineering (Professional)
• Microsoft Certified: Azure Data Engineer Associate
• GCP Certified: Professional Google Cloud Certified.
• AWS Certified Solutions Architect Professional
