onsite
Data Engineer II - Pearson
Data Engineer
Mid‑level Data Engineer building and maintaining scalable data pipelines and analytics solutions on Google Cloud Platform, leveraging strong SQL, data‑warehousing, and dimensional modeling expertise.
About the role
Key Responsibilities
- Design, develop, and maintain robust ETL pipelines that ingest, transform, and load data from multiple sources into cloud‑based data warehouses.
- Collaborate with business analysts and stakeholders to translate reporting and analytics requirements into scalable data models.
- Implement dimensional modeling techniques (star and snowflake schemas) to support BI and AI‑driven use cases.
- Optimize SQL queries and data warehouse performance for high‑volume, low‑latency reporting.
- Monitor pipeline health, troubleshoot issues, and ensure data quality and governance standards are met.
Requirements
- 2–4 years of hands‑on experience building data pipelines and data‑warehouse solutions.
- Strong proficiency in SQL and experience with relational databases (e.g., BigQuery, Snowflake, Redshift).
- Solid understanding of data‑warehousing concepts and dimensional modeling.
- Practical experience with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, or Composer.
- Proficiency in a scripting language such as Python for data manipulation and automation.