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Specialized data-platform role with hybrid/remote flexibility yields moderate competition among experienced candidates.
Medium because core data platform skills transfer across industries but require specialized modeling and multi-tenant experience.
High due to explicit 6+ years requirement plus mandatory deep data modeling, pipeline, and generative AI experience.
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Architect and build scalable, fault-tolerant data pipelines for batch and streaming data processing.
Own end-to-end data quality and observability including monitoring, alerting, testing, and documentation for data pipelines and models.
Design and evolve semantic and metric layers and architect enterprise-scale data solutions with advanced data modeling and Generative AI frameworks.
6+ years of software engineering experience with a strong focus on data architecture or system design.
Proven ability to architect complex data models and scale data platforms in multi-tenant environments.
Fluency in Python, Java, or Scala with solid software engineering fundamentals.
Expertise in data modeling paradigms such as dimensional modeling, Data Vault, or One Big Table.
Experienced in partnering with business teams and product leaders to translate ambiguous requirements into technical data solutions.
Comfortable working with multi-region batch and streaming pipeline architectures, including replication.
Skilled in applying data modeling principles with a strategic approach to grain selection, key strategy, and schema design in large-scale environments.