GCP Data Engineer
Summary
Build and maintain GCP-based data pipelines and warehouses using BigQuery, Composer, Python, and SQL to integrate and transform diverse data sources.
Responsibilities
- Design, create, code, and support a variety of data pipelines and models on GCP cloud technology
- Strong hand‑on exposure to GCP services like BigQuery, Composer, etc.
- Partner with business/data analysts, architects, and other key project stakeholders to deliver data requirements.
- Develop data integration and ETL (Extract, Transform, Load) processes.
- Support existing data warehouses & related pipelines.
- Ensure data quality, security, and compliance.
- Optimize data processing and storage efficiency, troubleshoot issues in the data space.
- Seek to learn new skills/tools utilized in the data space (ex: dbt, MonteCarlo, etc.)
- Exhibit excellent communication skills—verbal and written—and strong analytical skills with an Agile mindset.
- Demonstrate a strong affinity toward paying attention to details and delivery accuracy.
- Be a self‑motivated team player able to overcome challenges and achieve desired results.
- Work effectively in a global distributed environment.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related quantitative field.
- 3–5+ years of hands‑on experience in Data Engineering or Data Warehousing roles.
- At least 2 years specifically focused on Google Cloud Platform (GCP).
- Expert‑level knowledge of BigQuery (SQL, optimization, partitioning) and Cloud Composer (Apache Airflow) for orchestration.
- Proficiency in Python (specifically for ETL and Airflow DAGs) and advanced SQL.
- Strong experience in designing Star/Snowflake schemas and dimensional modeling.
- Proven track record of building and maintaining scalable data pipelines and managing data integration from diverse sources.
- Experience implementing data validation, cleansing, and security protocols (IAM, encryption).