01Key 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. .
