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Global brand, popular Data Engineer title, and mid-level (3+ years) experience increase candidate competition.
Core data engineering skills (Python, SQL, Airflow, GCP) are highly transferable across industries.
Explicit 3+ years and mandatory GCP, Python, SQL, and Airflow skills enforce moderate filtering.
Design, build, maintain, and troubleshoot moderately complex data pipelines using Airflow to ingest, transform, and aggregate data.
Develop and optimize data models and data quality tracking processes to ensure data accuracy and support analytical use.
Analyze and interpret large, complex datasets within an Agile, fast-paced development environment, delivering projects on time and budget.
3+ years of hands-on experience in software or data engineering with strong proficiency in Python and SQL.
2+ years of experience with enterprise relational databases and cloud warehouses (e.g., PostgreSQL, MySQL, BigQuery).
Hands-on experience building and orchestrating ETL/ELT pipelines using workflow tools like Apache Airflow and working within Google Cloud Platform (Cloud Storage, BigQuery).
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related technical field.
Experienced in managing data pipelines specifically using Apache Airflow and Google Cloud Composer DAGs in GCP environments.
Skilled in working independently with minimal supervision while maintaining effective communication with team and management.
Familiar with modern enterprise data platforms such as Snowflake or Databricks and understanding of streaming data frameworks and CI/CD pipelines is a plus.