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Mid-level data engineer in a metro, popular title, and known employer yields high applicant competition.
Core skills (SQL, Python, BigQuery, ETL) are highly transferable across industries.
Mandatory 4+ years plus BigQuery, DBT, Airflow and Python tech stack creates high shortlisting strictness.
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Design, develop, and maintain scalable data integration and analytics pipelines for enterprise reporting using Google BigQuery, Python, SQL, DBT, and Cloud Composer (Airflow).
Implement data quality checks, orchestration workflows, and deliver business-ready datasets aligned with enterprise data strategy.
Collaborate with cross-functional teams to integrate data from diverse enterprise systems such as ERP, CRM, E-commerce, and Order Management into a cloud data warehouse.
Bachelor's or master's degree in Computer Science, Data Engineering, Information Systems, or related technical field.
4+ years of hands-on experience in data engineering focused on data integrations, warehousing, and analytics pipelines.
Proficiency with Google BigQuery, Python, SQL, DBT, and Airflow/Cloud Composer for orchestration.
Work Experience Required: Minimum 4 years of data engineering experience.
Experienced in designing modular, maintainable, and reusable data transformation models using DBT, and optimizing BigQuery performance with partitioning, clustering, and query tuning.
Skilled in automating workflows and managing data pipeline execution using Cloud Composer (Airflow) with strong data quality and governance expertise.
Able to collaborate effectively with data analysts, BI developers, and product owners to deliver business-aligned, scalable data solutions within a cloud-based architecture.