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We are seeking a Lead / Senior Data Engineer to design, build, and optimize our core data infrastructure. In this role, you will bridge the gap between raw data and production-ready environments, ensuring our analytics systems are scalable, reliable, and high-performing. You will collaborate closely with Data Scientists to support advanced modeling and lead data engineering initiatives.
Job Responsibility
Build and orchestrate automated ETL/ELT pipelines for batch and real-time streaming data
Design and maintain scalable data lake and data warehouse structures
Partner with Data Scientists to optimize data pipelines, feature stores, and datasets required for statistical modeling
Tune and optimize complex SQL queries and data workflows for large-scale datasets
Establish technical best practices, ensure data quality, and mentor junior engineers
Requirements
Minimum 4+ years in Data Engineering, Big Data, or Data Architecture
Degree in Computer Science, Software Engineering, or a related quantitative field
Mastery of Python (including advanced Pandas and NumPy for data manipulation) and expert-level SQL
Strong familiarity with preparing data for statistical modeling and predictive frameworks (e.g., XGBoost, Regression, Decision Trees)
Experience with modern data stack tools (e.g., Spark, Airflow, dbt) and cloud data platforms (AWS, GCP, or Azure)