Job Description Key Responsibilities: Design and implement the enterprise-wide data architecture strategy, including hands-on development of proof-of-concepts for new technologies and frameworks Architect and actively develop complex distributed systems that can scale across multiple regions and handle diverse data workloads Develop, manage, and optimize ETL processes using Azure Data Factory to ensure accurate data integration across global databases Design, build, and maintain Microsoft SQL Server databases, ensuring data is well-organized, accessible, and secure Lead by example through hands-on development and implementation of advanced data processing frameworks that can be reused across multiple teams Define technical standards and best practices for data engineering across the organization through practical implementation and documentation Evaluate emerging technologies through proof-of-concept development and make recommendations for adoption or retirement of data technologies Identify and implement performance optimization strategies for ETL processes and reports to ensure optimal user experience Monitor and troubleshoot complex data processes to ensure uninterrupted service to global teams, including working occasionally outside regular business hours to support multiple time zones Create and maintain comprehensive technical documentation, architectural diagrams, and best practices Ensure data governance and compliance principles are maintained across all architectural decisions Communicate technical information to non-technical stakeholders effectively, tailoring the messaging as needed for diverse audiences Mentor and guide team members in technical best practices and architectural principles Collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders Required Technical Skills: Expert-level proficiency in SQL and database optimization techniques Hands-on expertise in Azure services, particularly Azure Data Factory, Azure SQL Database, and Azure Analysis Services Deep practical experience with Data Warehousing using Kimball and STAR schema Strong coding abilities in at least one programming language (Python, Java, or C#) Hands-on experience with distributed computing frameworks Practical experience implementing data streaming solutions Expert knowledge of performance tuning and optimization techniques Qualifications Qualifications: Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical field Significant, demonstrable hands-on data engineering experience, with at least 5 years in architectural roles preferably Proven experience as a Principal or Senior Data Engineer, with a focus on Microsoft SQL Server, Azure Data Factory, Power Automate and Power BI Demonstrated track record of designing and implementing large-scale distributed data systems Experience creating and implementing technical frameworks adopted by multiple teams Strong background in systems design, including handling complex data processing at scale Experience evaluating and implementing emerging technologies in production environments Leadership experience, with a focus on mentoring and coaching team members Strong problem-solving and troubleshooting skills with a hands-on approach Excellent communication and collaboration skills Willing to work flexible hours to support a global business What Sets You Apart: Contributions to open-source projects or internal shared libraries Experience with real-time data processing and streaming architectures Track record of solving complex technical challenges at scale History of successful technical mentorship Experience working in a global, distributed team environment Additional Information Why Join Us: Work in a dynamic and innovative team driving real business impact.Opportunities for professional growth and development in a leadership role.Collaborative culture and cross-functional engagement with various teams and stakeholders.Competitive salary and benefits.