Lead Data Architect

Empowers Staffing is recruiting an experienced Lead Data Architect for a financial services organization. This is a senior technical leadership position responsible for defining and advancing enterprise data architecture while helping modernize a large-scale cloud data environment. The successful candidate will establish architecture standards, guide data engineering teams, design scalable data solutions, strengthen governance and security, and help prepare the organization’s data environment for advanced analytics and AI. The position requires someone who can operate at the architecture and strategy level while remaining technically hands-on., Define and evolve enterprise data architecture, standards, models, and design patterns. Lead architecture and solution design for modern cloud-based data platforms. Design scalable environments supporting analytics, reporting, operational data, and advanced data use cases. Establish architectural standards for data integration, security, governance, quality, performance, and reliability. Provide technical leadership and mentorship to Data Engineers and other technical professionals. Serve as a senior escalation resource for complex data-platform and engineering issues. Participate in the architecture, development, and review of data pipelines and integration processes. Guide ETL/ELT architecture and engineering practices. Lead modernization of legacy and existing data environments. Improve platform scalability, resiliency, performance, and operating efficiency. Partner with technology, analytics, risk, compliance, and business teams to translate requirements into practical data solutions. Establish approaches for secure and governed enterprise data access. Help ensure data solutions meet regulatory, security, privacy, and internal governance requirements. Evaluate new technologies and recommend improvements to the organization’s data ecosystem. Support cloud migration and data-platform transformation initiatives. Advance organizational readiness for AI, machine learning, advanced analytics, and intelligent automation. Help establish architecture that supports both traditional data warehousing and modern lakehouse approaches. Provide technical direction throughout solution design, implementation, and ongoing platform evolution.

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical discipline. 10+ years of professional experience in data engineering, data architecture, data platform engineering, or closely related disciplines. At least 5 years of experience designing and implementing enterprise-scale cloud data platforms. Strong experience with cloud-based data services. Advanced SQL skills. Strong Python experience. Experience with distributed data-processing technologies such as Spark. Strong knowledge of ETL/ELT architecture and frameworks. Experience designing modern data warehouse, data lake, or lakehouse environments. Strong understanding of enterprise data modeling and architecture patterns. Experience implementing data governance, data quality, security, and access control standards. Experience designing scalable and resilient enterprise data solutions. Demonstrated technical leadership experience. Experience mentoring or providing architectural direction to Data Engineers. Experience working within regulated, security-sensitive, or highly governed environments. Highly Desirable Experience Experience with several of the following would be particularly valuable: Microsoft Azure data technologies Databricks Snowflake Microsoft Fabric Power BI Real-time or streaming data architectures AI/ML platforms Enterprise cloud migrations Large-scale data modernization AI enablement initiatives Relevant cloud, data-engineering, architecture, or data-platform certifications are also