Solution Engineer Senior - Data Scientist

Job description

Key Responsibilities: • Design, build, and support enterprise data, analytics, AI, and machine learning solutions using the Databricks Lakehouse Platform • Design and Develop scalable data pipelines, AI/BI dashboards, Databricks Apps, Lake base applications, and data products to meet business and analytical requirements. • Collaborate with business stakeholders, architects, and product teams to define functional and technical solution requirements. • Design enterprise data architectures, integrations, and workflows that align with governance, security, and performance standards. • Develop and operationalize machine learning, Generative AI, RAG, and agentic AI solutions using Databricks AI capabilities. • Deliver trusted analytics and insights through governed data products, dashboards, and self-service analytics. • Evaluate existing application ecosystems (including Oracle Supply Chain Planning and S&OP) and recommend modernization opportunities using Databricks. • Lead solution design, implementation, testing, support, and continuous improvement while ensuring best practices for scalability, reliability, and cost optimization \\*Qualifications and Competencies Experience: • 5+ years of experience designing and delivering enterprise data, analytics, AI, or engineering solutions. • Proven experience with the Databricks Lakehouse Platform, including Unity Catalog, Delta Lake, Databricks SQL, AI/BI Dashboards, Databricks Apps, Lakebase, Workflows, and MLflow. • Hands-on experience building production-grade GenAI, RAG, multimodal AI, agentic workflows, Vector Search, and MLOps solutions using Databricks, Azure OpenAI, AWS, Azure, or GCP. • Strong proficiency in PySpark, SQL, Python, data engineering, machine learning, and cloud-native architectures. • Experience with enterprise application integration, Agile delivery, and the full software development lifecycle. • Excellent stakeholder management, problem-solving, and communication skills.