Join a leading technology practice focused on unlocking the value within vast data ecosystems. Our team provides strategic guidance and implementation services for data management, transforming disparate data sources into actionable insights. We specialize in business intelligence, data management, performance management, and next-generation analytics, including big data, cloud, cognitive computing, and machine learning.

You will define and implement enterprise data architecture aligned with business objectives and technology roadmaps. This includes designing scalable, secure, high-performance data platforms using cloud technologies and modern architectural principles. Your role involves leading the architecture and implementation of Data Warehouses, Data Lakes, Lakehouse platforms, and Data Mesh solutions. You will also develop comprehensive data models, define integration and migration strategies, and establish frameworks for data governance, quality, and Master Data Management.

Key responsibilities include overseeing real-time and batch data processing architectures, collaborating with stakeholders to drive data initiatives, and assessing/optimizing existing data platforms. You will also define and enforce data security, privacy, and compliance standards, alongside providing technical leadership and architectural guidance to data teams. Evaluating emerging data technologies and ensuring adherence to best practices are also integral parts of this role.

We are seeking a seasoned professional with 10-14 years of experience in data engineering, data architecture, or related technology fields, demonstrating significant expertise in architecture and design. Strong command over enterprise data architecture patterns, integration strategies, and modern data platform design is essential. Proven experience with Data Warehousing (including medallion architecture), Data Lakes, Lakehouse, and Data Mesh architectures is required.

Proficiency in conceptual, logical, and physical data modeling is a must. Hands-on experience with cloud platforms like Snowflake (required) and AWS (required), alongside traditional SQL, is crucial. Expertise in ETL/ELT, data integration, transformation, and migration strategies, coupled with a deep understanding of data governance, metadata management, data quality, and MDM, is expected. Experience designing batch, real-time, and event-driven/CDC data processing architectures, along with knowledge of enterprise data security, privacy, regulatory compliance, and access controls (especially PII/PHI), is also necessary. Familiarity with data platform performance optimization, scalability, reliability, and cost management is vital.