Design, build, test, and maintain data transformation pipelines that convert raw Computer Vision-generated transactional data into clean, reliable aggregated datasets.
Define and document data models, metrics, and aggregation logic.
Ensure interpretability and accuracy of aggregated data.
Analyze data to identify biases, gaps, and CV-pipeline artifacts, and design compensations where needed.
Develop internal tools for monitoring, debugging, validating assumptions, and helping other teams reason about aggregated data.
Collaborate with product managers to gather requirements and assess feasibility or constraints.
Collaborate with upstream CV teams to define data contracts and ensure input data quality.
Collaborate with downstream teams (e.g., web backend engineers) to design aggregates that meet product constraints and performance needs.

Bachelor’s degree in Computer Engineering or Computer Science.
Strong understanding of data modeling and scalable custom ETL/ELT pipeline design.
Detail-oriented with strong systems-thinking skills and the ability to anticipate data caveats and evolving requirements.
Comfortable working with incomplete or noisy data and making sound technical judgments under uncertainty.
Proficiency in Python for data processing, analysis, and tool-building.
Familiarity with MongoDB and PostgreSQL (or willingness to learn both).
Comfortable working in a Unix/Linux development environment.
Understanding the needs and challenges of working in a startup environment.
Knowledge of data-driven mall/retail analytics or footfall systems is a plus.

Data Engineer

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