· Partner with client stakeholders to understand business priorities, uncover root causes, define requirements, and translate complex needs into actionable data solutions.
· Lead problem-solving activities across ambiguous and complex environments, evaluating options, risks, dependencies, and trade-offs.
· Design, build, test, and support scalable data pipelines, lakehouse solutions, and curated data products using Microsoft Fabric and Azure Databricks.
· Develop reliable data transformations and engineering components using Python, PySpark, and SQL.
· Facilitate discovery sessions, technical workshops, backlog refinement, solution walkthroughs, and stakeholder updates.
· Manage stakeholder expectations through clear communication, proactive issue management, and transparent delivery reporting.
· Apply sound engineering practices for data quality, observability, security, governance, performance optimization, and operational support.
· Contribute to architecture decisions, estimates, delivery plans, technical documentation, and client presentations.
· Collaborate with architects, analysts, data scientists, AI engineers, and delivery teams across onshore and offshore environments.
· Support and mentor junior team members through technical guidance, reviews, and knowledge sharing.
· Explore opportunities to integrate AI engineering capabilities into data solutions, including Microsoft Foundry and Microsoft Copilot Studio.