Resident Solution Architect - MLOPS Expert

RSA - MLOps Expert
Resident Solutions Architect
MLOps Expert
About the Role
We’re looking for a Resident Solutions Architect who is passionate about solving complex data challenges and building scalable, modern data platforms. You’ll design and implement data solutions that enable advanced analytics and machine learning, while also leading projects and guiding clients toward best practices in modern cloud architecture and MLOps.
Key Responsibilities
● Lead the architecture, design, and delivery of scalable data solutions using modern data and cloud technologies
● Develop and optimize data pipelines using tools like Databricks, DLT, and Autoloader within the Medallion Architecture framework
● Develop ML systems from whiteboard to feature selection, hyperparameter tuning, and training ● Integrate machine learning models into production environments using MLOps best practices, e.g. CI/CD, model registry, monitoring
● Collaborate with cross-functional teams to define data strategies, establish governance via Unity Catalog, and ensure data quality and lineage
● Apply deep expertise in query tuning, performance optimization, and cost management (TCO) to maintain system efficiency
● Support large-scale migrations and modernization projects across cloud platforms ● Act as a trusted consultant, guiding clients through decisions, articulating business value, and “selling the solution”
● Mentor team members, foster a growth mindset, and contribute to a collaborative Databricks-aligned culture
Required Qualifications
● 5+ years of experience in data engineering and project leadership roles.
● Experience integrating analytics and AI/ML workflows into enterprise data platforms ● Proven hands-on experience with the Databricks Platform, including:
○ Unity Catalog
○ DLT / Autoloader
○ DBSQL
○ Photon
● Data Science and MLOps experience demonstrating competence in:
○ Feature Engineering
○ Training
○ Hyperparameter tuning
○ ML Ops Best practices (CI/CD, model registry, monitoring, etc.)
● Deep familiarity with CI/CD pipelines, git integrations, and Terraform-based infrastructure as code ● Practical understanding of MLOps concepts, including model deployment, monitoring, and retraining workflows
● Cloud expertise in Azure, AWS, and/or Google Cloud Platform (Google Cloud Platform)
● Successful consulting experience delivering end-to-end data solutions to enterprise clients ● Excellent communication and stakeholder management abilities
● Strong problem-solving and analytical mindset
● Collaborative, team-oriented, and a good fit for Databricks’ culture
● Self-motivated with a growth mindset and ownership mentality
Preferred Qualifications
● Databricks Certified Data Engineer Professional or equivalent advanced Databricks certifications ● Experience with large-scale data migration, streaming pipeline design, or AI-assisted analytics ● Background working across enterprise and technical consulting environments ● Familiarity with price/performance optimization techniques