This is not a purely conceptual architecture position. The architect will work directly with business, product, data, and engineering stakeholders to understand complex and sometimes ambiguous problems, investigate existing systems and data, rapidly design appropriate solutions, and remain closely involved through implementation and production deployment.
The ideal candidate combines enterprise-level architectural thinking with the technical depth of a senior hands-on engineer.
Work directly with business and technical stakeholders to understand complex data and technology problems.
Translate ambiguous business requirements into actionable architecture and engineering solutions.
Rapidly understand existing data ecosystems, applications, integrations, data flows, and constraints.
Define target-state architectures for enterprise data solutions.
Architect scalable solutions using Azure Databricks, ADLS, ADF, Fabric/Synapse, and related Azure technologies.
Define Lakehouse, Delta Lake, batch, streaming, and analytical architecture patterns.
Remain hands-on with Python, PySpark, SQL, Databricks, and data engineering as required.
Develop or guide rapid prototypes to validate architecture decisions.
Define ingestion, transformation, storage, consumption, API, and integration patterns.
Architect solutions spanning data platforms, APIs, applications, analytics, and AI/ML consumers.
Define logical and physical data models.
Establish standards for data quality, metadata, lineage, security, governance, and observability.
Design for scalability, resiliency, performance, security, and cost optimization.
Conduct architecture, design, and code reviews.
Troubleshoot complex cross-platform technical issues.
Provide technical direction and hands-on guidance to Data Engineers and FDE teams.
Partner with AI/ML, DevOps, security, product, and application engineering teams.
Own technical outcomes from problem discovery through production implementation.
10+ years of progressive Data Engineering/Data Architecture experience.
Strong Microsoft Azure architecture experience.
Azure Databricks.
Python and PySpark.
Advanced SQL.
ADLS Gen2.
Azure Data Factory.
Lakehouse and Delta Lake architecture.
Data modeling.
ETL/ELT and distributed data processing.
API and enterprise integration architecture.
CI/CD and modern engineering practices.
Data security, governance, metadata, lineage, and quality.
Experience architecting enterprise-scale data platforms.
Strong stakeholder-facing communication and technical leadership.
Ability to move between architecture discussions and hands-on technical problem solving.