27 days ago
Remote, Armenia or Yerevan, ArmeniaSenior
Responsibilities
- Design end-to-end data architectures and solutions on Google Cloud Platform.
- Build ingestion, transformation, and data processing pipelines.
- Work with structured and unstructured data.
- Implement security, observability, and data quality practices.
- Collaborate with business and technology teams to deliver production-ready solutions.
Requirements
- Solid experience in Data Engineering and data architecture.
- Hands-on experience with Google Cloud Platform.
- Advanced knowledge of BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
- Proficiency in Python and SQL.
- Experience with dbt, Airflow, or Cloud Composer.
- Knowledge of ETL/ELT, data modeling, and Medallion architectures.
- Experience with Terraform, CI/CD, or infrastructure-as-code tools.
- Intermediate to advanced English proficiency.
- More than one year of relevant work experience and a solid understanding of programming, software design, and software development principles.
- Preferred experience with Vertex AI, Document AI, OCR, or LLMs.
- Preferred knowledge of document processing and unstructured data.
- Preferred experience with IAM, security, and data governance in GCP.
- Preferred knowledge of batch and streaming processing.
- Preferred Google Cloud Professional Data Engineer certification.
Benefits
- Virtual-work expense reimbursement.
- OSDE private healthcare plan.
- Megatlon and Fiter benefits.
- 70% discount on CUI English, French, and Portuguese courses.
- Courses and certifications through Udemy and Next.
Tech Stack
Categories
Data Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.