תיאור המשרה
Gett is a Ground Transportation Solution with the mission to organize all the best mobility providers in one global platform with great UX - optimizing the entire experience from booking and riding to invoicing and analytics, to save businesses time and money.
We are looking for a talented Senior Data Engineer to join us.
As a Data Engineer at Gett, you will be a key member of the data team, at the core of a data-driven company, developing scalable, robust data platforms and data models and providing business intelligence. You will work in an evolving, challenging environment with a variety of data sources, technologies, and stakeholders to deliver the best solutions to support the business and provide operational excellence.
If you are passionate about data, a team player, and proactive, we want to hear from you.
Responsibilities:
- Design, Develop & Deploy Data Pipelines and Data Models on various Data Lake / DWH layers
- Ingest data from and export data to multiple third-party systems and platforms (e.g., Salesforce, Braze, SurveyMonkey).
- Architect and implement data-related microservices and products
- Ensure the implementation of best practices in data management, including data lineage, observability, and data contracts.
- Maintain, support, and refactor legacy models and layers within the DWH
Requirements
- 5+ years of experience in software development, data engineering, or business intelligence developement
- Proficiency in Python - A must.
- Advanced SQL skills - A must
- Strong background in data modeling, ETL development, and data warehousing - A must.
- Experience with big data technologies, particularly Airflow - A must
- Familiarity with tools such as Spark, Hive, Airbyte, Kafka, Clickhouse, Postgres, Great Expectations, Data Hub, or Iceberg is advantageous.
- General understanding of cloud environments like AWS, GCP, or Azure - A must
- Experience with Terraform, Kubernetes (K8S), or ArgoCD is advantageous.
- A bachelor’s degree in Computer Science, Engineering, or a related field is advantageous but not mandatory
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