Posted Apr 21, 2026
As a Senior Technical Consultant with expertise in Databricks and Machine Learning, you will be responsible for designing and implementing end-to-end data and machine learning solutions. Your role will involve developing and optimizing data pipelines, ETL/ELT processes, and ML workflows. You will collaborate with cross-functional teams to gather requirements and translate them into technical solutions. Additionally, you will provide technical leadership in data engineering and ML architecture, ensuring data quality, governance, and security standards are met. Your ability to optimize performance, scalability, and cost-efficiency of data platforms will be crucial in this role. Key Responsibilities:
Qualifications Required:
Strong hands-on experience with Databricks
Proven experience in Machine Learning (model development, training, deployment)
Proficiency in Python and SQL
Experience with Apache Spark / PySpark
Strong understanding of data engineering concepts and modern data architectures
Experience working with cloud platforms (e.g., Azure, AWS, or GCP)
Ability to design scalable and efficient data and ML solutions
Strong problem-solving and analytical skills
Excellent communication and stakeholder management skills As a Senior Technical Consultant with expertise in Databricks and Machine Learning, you will be responsible for designing and implementing end-to-end data and machine learning solutions. Your role will involve developing and optimizing data pipelines, ETL/ELT processes, and ML workflows. You will collaborate with cross-functional teams to gather requirements and translate them into technical solutions. Additionally, you will provide technical leadership in data engineering and ML architecture, ensuring data quality, governance, and security standards are met. Your ability to optimize performance, scalability, and cost-efficiency of data platforms will be crucial in this role. Key Responsibilities:
Design and implement end-to-end data and machine learning solutions using Databricks
Develop and optimize data pipelines, ETL/ELT processes, and ML workflows
Build, train, and deploy machine learning models for real-world business use cases
Collaborate with cross-functional teams to gather requirements and translate them into technical solutions
Provide technical leadership and best practices in data engineering and ML architecture
Optimize performance, scalability, and cost-efficiency of data platforms
Ensure data quality, governance, and security standards are met
Support troubleshooting, debugging, and continuous improvement of data and ML systems
Stay updated with the latest advancements in Databricks and ML technologies
Qualifications Required:
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