Own design and development of enterprise-scale Data Engineering and AI solutions
Design, build, and maintain scalable and efficient data pipelines to ingest, process, and store large volumes of data
Creating and optimizing robust data models and architectures that support advanced analytics, reporting, and machine learning initiatives
Write production-grade SQL and Python scripts for data transformation, pipeline automation, and integration with upstream and downstream systems
Instrument data pipelines with robust quality frameworks
Contribute to AI integration workstreams, including building data tables and pipeline structures that support LLM-generated insight delivery

4+ years of professional experience in data engineering or analytics engineering
Expert-level SQL, including window functions, recursive CTEs, complex multi-level aggregations, and query performance profiling in a cloud data warehouse environment
Intermediate Python proficiency for data pipeline scripting, ETL/ELT automation, and lightweight data wrangling using pandas, numpy, or equivalent libraries
Demonstrated experience designing data architecture that supports analytical reporting at enterprise scale—including dimensional modeling, object rationalization, and parametric configuration layer design.

Data Engineer

Key skills