concurrency - Data Architect
Requirements
• Over 7 years of experience designing and delivering data solutions, with experience operating in an architecture or senior technical leadership role • Deep expertise in modern data architectures, including lakehouse, ELT/ETL orchestration, data modeling, and analytics platforms on Microsoft Azure • Proven ability to design scalable data solutions supporting structured, semi-structured, and unstructured data • Strong hands-on experience with technologies such as Azure Data Factory / Fabric Pipelines, Databricks (PySpark), SQL, and cloud-native data services • Demonstrated experience leading technical discovery, requirements gathering, and architecture design in client-facing environments • Strong understanding of data governance, security, and compliance considerations (e.g., RBAC, data classification, lineage) • Experience leveraging AI‑augmented delivery techniques to improve solution quality and productivity, with the ability to establish usage standards and lead by example through hands‑on application. • Ability to communicate complex architectural concepts clearly to both technical and non-technical audiences • Comfort operating with a high degree of autonomy while collaborating across cross-functional teams • ## What Will Set You Apart • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field • Experience designing enterprise-scale data platforms using Microsoft Fabric, Azure Synapse, or multi-cloud data ecosystems • Exposure to AI-enabled data patterns such as vector search, RAG architectures, or analytics supporting generative AI use cases • Relevant certifications such as Azure Data Engineer Associate (DP‑203), Fabric Engineer Associate, or architecture-focused credentials
Responsibilities
• Lead end-to-end technical discovery and architecture design for complex data and analytics initiatives, translating ambiguous business goals into scalable, secure data solutions • Architect modern data platforms on Azure, including lakehouse, streaming, and analytics architectures using services such as ADLS, Databricks, Fabric, Synapse, and related tooling • Define and document reference architectures, design patterns, and implementation standards that are reusable across clients and engagements • Serve as a trusted technical advisor to client stakeholders, guiding architectural decisions, tradeoffs, and roadmaps aligned to business outcomes • Balance ideal-state architecture with real-world constraints including cost, timeline, data maturity, and team skill sets • Oversee and review solution implementations to ensure architectural integrity, performance, scalability, and security best practices • Partner with delivery teams to resolve complex technical challenges and act as an escalation point for architecture-related decisions and positive client sentiment • Integrate AI-augmented delivery practices into solution design and implementation, while exercising strong engineering judgment and governance • Mentor engineers and senior engineers through architecture reviews, design sessions, and ongoing coaching • Contribute to pre-sales activities including technical discovery workshops, solution shaping, and proposal support
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