5 days ago
Remote, Armenia or Yerevan, ArmeniaSenior
Responsibilities
- Design and develop data solutions based on Databricks.
- Build and maintain scalable data pipelines.
- Implement DataOps practices and automation.
- Define data governance and data quality standards.
- Collaborate with business and technology teams to deliver analytics solutions.
Requirements
- More than 7 years of experience in data engineering.
- Strong experience with Databricks and Apache Spark, including PySpark and Spark SQL.
- Experience with dbt, Airflow, or Databricks Workflows.
- Proficiency in SQL and Python.
- Knowledge of Lakehouse architecture and data modeling.
- Experience working with AWS, Azure, or Google Cloud.
- Intermediate or advanced English proficiency.
- Preferred experience with Kafka, Fivetran, or Pub/Sub.
- Preferred knowledge of Unity Catalog and Immuta.
- Preferred experience with Power BI.
- Databricks Data Engineer Professional certification is desirable.
- Knowledge of AI/ML or generative AI solutions is desirable.
Benefits
- Virtual-work expense reimbursement.
- OSDE private health coverage.
- Benefits at Megatlon and Fiter.
- 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.