- 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.