Responsibilities: Data Infrastructure: Build, implement, and maintain scalable data pipelines and storage architectures. Data Quality: Maintain strong data integrity by ensuring reliability, consistency, and accuracy across all data processes. Performance Optimization: Enhance system efficiency by tuning data processing workflows and improving large-scale performance. Process Improvement & Mentoring: Strengthen data engineering practices while providing guidance and support to junior engineers. Cross-Functional Collaboration: Partner with business analysts, data scientists, and backend teams to deliver timely and actionable data solutions.
Qualifications:
5+ years' experience in data engineering or backend roles, with strong programming skills in Python or Java/Scala. Hands-on experience with big data tools: Spark, Flink, Kafka, Airflow, and cloud platforms (AWS, GCP, Azure) proficient in SQL. Skilled in designing and maintaining data models, warehouses, and ETL/ELT pipelines for...