Back
Metro-based, mid-level Data Engineer role with 3–5 years at a known multinational increases competition.
Role requires specific GCP/BigQuery data engineering expertise, limiting cross-industry transferability.
Multiple mandatory technical skills and explicit 3–5 year requirement make screening stringent.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and development of scalable, secure, high-performing data pipelines on Google BigQuery for structured and semi-structured enterprise data.
Build analytics-ready datasets by transforming raw data using DBT, Python, and SQL to support reporting and advanced analytics.
Mentor junior engineers, enforce data quality frameworks, implement workflow orchestration with Airflow, and establish best practices across the enterprise data engineering ecosystem.
3-5 years of hands-on data engineering experience with expertise in cloud data warehousing and pipeline development.
Expertise in Google BigQuery, Python, SQL, DBT, and Airflow/Cloud Composer.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related technical field.
Work Experience Required: 3-5 years as explicitly mentioned
Proven ability to architect and deliver enterprise-grade ETL/ELT pipelines and scalable data architectures on Google Cloud Platform.
Experienced in Agile environments with strong skills in data quality frameworks, automation, monitoring, and continuous improvement.
Comfortable leading technical discussions, mentoring engineers, and collaborating cross-functionally to align data solutions with business needs.