Azure Data Engineer – Python & Databricks

Candidate Description

A versatile data engineering professional with six years of hands-on experience designing and delivering scalable, cloud-native data platforms across Azure and AWS. This individual excels in crafting lakehouse architectures, medallion data models, and metadata-driven pipelines, bringing deep proficiency in Python, PySpark, SQL, Databricks, and related Azure services. Their work spans finance comparison, manufacturing, energy, and enterprise domains, underpinned by strong analytical acumen and a commitment to data governance.

Demonstrating technical depth, they have architected high-volume ingestion and transformation pipelines for a Financial Services Company, automated analytics workflows at a Manufacturing Company, and built predictive models for an Energy Company. Adept at leveraging tools such as Power BI, Power Platform, and Azure Data Lake Gen 2, they consistently deliver governed, analytics-ready datasets that empower business stakeholders. Their achievements include migrating on-premise workloads to the cloud, implementing reusable medallion patterns, and eliminating significant manual effort through automation.

Beyond technical delivery, this professional thrives in collaborative, cross-functional environments, translating complex requirements into robust data solutions and mentoring teams on best practices. Their adaptability across industries—from Financial Services to Energy—combined with formal certifications like Microsoft Power Platform Fundamentals, positions them as a high-impact contributor capable of accelerating data-driven transformation initiatives for any organisation.