Carbon60

• Provide deep technical expertise and leadership across a range of cloud data technologies. • You will be the go-to person for driving tool selection, resolving complex engineering issues, and guiding best practices during engagements. • Lead the design and implementation of data platforms to meet customers' business requirements. • Lead whiteboard design sessions with internal and external team members. • Identify and communicate technical risks as they emerge over the course of a project. • Work closely with Principal Consultants to extract project requirements during technical discovery sessions, define deliverables to meet those requirements, and break down those deliverables into a technical roadmap. • Lead teams of data engineers to execute project roadmaps. • Provide guidance on technical tasks, priorities, and technical assistance when needed. • Manage scope within customer engagements. Identify changing requirements as they arise, determine their impact on scope, and ensure all stakeholders are aware and agree with the changes. • Maintain a close working relationship with the customer, as a "Trusted Advisor". Set clear expectations, challenge assumptions, solicit feedback, and take ownership of project deliverables. • Establishing credibility and building impactful relationships with our customers. • Architect end-to-end data solutions on Microsoft Fabric, including Lakehouse, Data Warehouse, Real-Time Intelligence, and Data Factory components. • Lead technical design sessions and produce architecture artefacts: solution designs, data flow diagrams, and runbooks. • Build and optimise data pipelines using Azure Data Factory and Fabric Data Engineering workloads. • Define and enforce data governance frameworks — policies, stewardship models, and access controls — leveraging Microsoft Purview. • Implement data lineage tracking end-to-end, ensuring full auditability across ingestion, transformation, and consumption layers. • Establish data quality rules, monitoring, and remediation processes across OneLake and downstream analytics layers. • Collaborate with data product owners, engineers, and business stakeholders to translate requirements into scalable platform designs. • Champion best practices for CI/CD, infrastructure-as-code (Bicep / Terraform), and DevOps within the Azure data space. • Provide technical mentorship to engineering teams and contribute to internal standards and reusable accelerators.