Architect and implement end-to-end data pipelines and AI-powered BI solutions across cloud platforms. Collaborate with cross-functional teams to translate business needs into scalable AI/ML and data solutions. Design for performance, cost-efficiency, and maintainability in cloud-native environments. Drive adoption of MLOps practices and ensure robust model deployment and monitoring. Champion data governance, privacy, and compliance across all AI and BI initiatives. Lead solution reviews, technical workshops, and roadmap planning for AI maturity. Data Engineering Expertise in data modeling, ETL pipeline design, and orchestration. Hands-on experience with Apache Spark, Databricks, Airflow, Kafka. Strong SQL skills and familiarity with Snowflake, BigQuery, or Redshift. Experience with Azure ML, SageMaker, or Vertex AI. Experience implementing data lineage, cataloging, and access control. Strong solution architecture mindset with the ability to align technical solutions to business goals. Excellent communication skills to explain complex AI concepts to non-technical stakeholders. Proven ability to work across data science, engineering, product, and business teams. Strategic thinker with a focus on ROI, feasibility, and data readiness. Change agent who promotes AI literacy, manages expectations, and drives data culture. Bachelor's or Master's degree in Computer Science, Data Science, or related field. 8+ years in data engineering, BI, or AI solution architecture roles. Certifications in cloud platforms (Azure, AWS, GCP) or ML tools are a plus. Python coding experience
