We are seeking a Data Engineer with strong experience in the Google Cloud Platform (GCP) ecosystem to design, build, and maintain scalable data pipelines and analytics solutions. The ideal candidate will have expertise in cloud-based data engineering, ETL/ELT development, data warehousing, and modern data architectures.
Responsibilities
- Design, develop, and maintain data pipelines on GCP.
- Build and manage ETL/ELT processes for structured and unstructured data.
- Develop and optimize data models and data warehouses.
- Integrate data from multiple source systems into centralized analytics platforms.
- Ensure data quality, governance, security, and compliance.
- Monitor and optimize data pipeline performance and costs.
- Work closely with business stakeholders, analysts, and application teams.
- Support reporting and analytics initiatives leveraging cloud data platforms.
Required Skills
- 3+ years of experience in data engineering.
- Experience with Python and/or Java.
- Hands‑on experience with:
- BigQuery
- Pub/Sub
- Experience building batch and real‑time data pipelines.
- Understanding of data warehousing and dimensional modeling.
Preferred Skills
- GCP Professional Data Engineer certification.
- Experience with Databricks or Snowflake.
- Experience with CI/CD and DevOps practices.
- Knowledge of machine learning data pipelines.
- Experience with container technologies such as Kubernetes and Docker.
Typical Deliverables
- Data lake and warehouse solutions
- Real-time streaming architectures
- Analytics-ready datasets
- Data quality and governance frameworks
- Performance optimization and cost management