You’ll need
Education
✓Bachelor’s degree in computer science, Engineering, or a related field from an accredited institution
Qualifications
✓7+ years of experience in data architecture or data engineering with demonstrated ownership of large-scale data systems.
✓Strong experience designing enterprise data architectures for analytics and advanced analytical workloads, not just individual pipelines.
✓Deep understanding of data modeling, data warehousing, and Lakehouse architectures , including trade-offs between performance, cost, and governance.
✓Proficiency in SQL and at least one general-purpose programming language such as Python or Java , with strong grasp of distributed data processing concepts.
✓Hands-on experience with Spark-based platforms or equivalent distributed processing technologies .
✓Experience working with cloud data platforms on Azure, AWS, or GCP, with the ability to adapt architectural patterns across cloud ecosystems.
✓Solid understanding of how data architectures support machine learning and AI , including feature engineering, data versioning, and lifecycle management.
✓Familiarity with feature stores, semantic layers, knowledge graphs, or metadata-driven architectures used to enable analytics and AI.
✓Strong communication skills, with the ability to influence technical direction and clearly explain architectural decisions to engineering teams and leadership.
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About the role
In this role, the focus extends far beyond hands‑on implementation. The Senior Data Architect will drive enterprise‑level decision‑making related to data modeling, engineering best practices, governance and compliance integration, and long‑term platform sustainability.