Data Engineer

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 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 be working 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
  
  

• Minimum of 3 years of experience in software development, data engineering, or business intelligence
• 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