Back
Metro location, popular mid-level role, broad cloud data stack, and strong employer brand increase competition.
Core data engineering skills transfer across industries, but GCP/BigQuery specialization raises domain sensitivity moderately.
Explicit 3–5 years and mandatory BigQuery, DBT, Airflow, Python and SQL create strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead the design and development of scalable, secure cloud-based data pipelines using Google BigQuery and tools like Python, SQL, DBT, and Airflow.
Ensure high data quality and deliver analytics-ready datasets for enterprise systems including ERP, CRM, and ecommerce.
Mentor junior engineers and establish best practices for data engineering workflows and enterprise data strategy.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related technical field.
3-5 years of hands-on data engineering experience with expertise in cloud data warehousing and pipeline development.
Expert-level skills in Google BigQuery, Python, SQL, DBT, and Airflow/Cloud Composer.
Experience building enterprise-grade ETL/ELT pipelines and implementing data quality frameworks.
Experienced in architecting and optimizing large-scale data integration pipelines on Google Cloud Platform.
Proficient in modular data transformations with DBT and workflow orchestration automation using Airflow.
Able to collaborate cross-functionally and lead technical mentoring and best practice standardization in an Agile environment.