Senior Databricks/ML Technical Consultant

Job not on LinkedIn

🕒 April 10

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

DysrupIT

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🏢 Enterprise

☁️ SaaS

🔒 Cybersecurity

Enterprise • SaaS • Cybersecurity

DysrupIT is a global cloud services and IT solutions firm that helps organizations adopt cloud technologies and transition to as-a-Service business models. The company provides enterprise cloud, managed services, application engineering, cybersecurity, and data analytics & information management, serving SMBs through multinational enterprises with Microsoft and other cloud platforms. DysrupIT also emphasizes community impact, talent development, and long-term partnerships to deliver secure, scalable, and business-aligned technology outcomes.

📋 Description

• 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 • Work with large-scale structured and unstructured datasets • 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

🎯 Requirements

• 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.