Data Engineer (middle)

inDrive is an international technological platform for transport and personal services. We are one of the top 2 mobile travel booking services in the world with over 150 million installs, over 2 billion trips, 800+ cities in 40+ countries.

inDrive is a product used by tens of millions of people every month. They make urban or intercity trips, order cargo transportation or courier delivery, look for work and call handymen to provide household services.

inDrive employs more than 3,000 employees, of which 550+ are developers, divided into 50+ cross-functional teams.

We are looking for a Data engineer who will help build a Data Warehouse as part of a team that develops various Data solutions for such business areas as Fintech, Safety, ESG, Government Relation and etc. We expect you to participate in architecture construction, data modeling, share knowledge and receive this knowledge. We are actively building our Data Warehouse and we know for sure that this part of the project is one of the most important parts of the product.

We create data solutions for Geo, Fintech, Safety, ESG, Government Relations, GDPR, and other areas. We are currently actively building a Data Warehouse — a key part of the product. We work with cutting-edge technologies (GCP, AWS, Airflow, Kafka, K8s) and make infrastructure and architectural decisions based on data.
One of the key areas is the development of a personalization system for our users. We are building a large-scale data infrastructure for analytics, machine learning, and real-time recommendations.

Our tech stack:

• Languages: Python, SQL, Scala, Go
• Frameworks: Spark, Apache Beam Storage and
• Analytics: BigQuery, GCS, S3, Trino, other GCP and
• AWS stack components Integration: Apache Kafka,
• Google Pub/Sub, Debezium, Zero ETL, Firehose ETL: Airflow2
• Infrastructure: Kubernetes, Terraform Development: GitHub, GitHub Actions, Jira

What tasks remain to be solved:

• Develop the data driven culture within the company
• Develop processes for data processing, storage, cleaning, and enrichment
• Design and maintain data pipelines from collection to consumption
• Develop APIs (REST, gRPC) for high load services
• Create infrastructure for storing and processing large datasets on K8S, Terraform
• Automate testing, validation, and monitoring of data
• Participate in system design and architectural decision making

We expect from the candidate:

• Who we are looking for Expert in Python 3.7+, experience with PySpark Deep knowledge of SQL
• Extensive experience building ETLs with Airflow2 Industrial experience with Kubernetes
• Understanding of data processing principles and algorithms
• Excellent knowledge of OOP, design patterns, clean architecture
• Proactivity, responsibility, and the ability to take ownership
• Would be a plus: Experience with high load services DevOps skills and CI/CD automation experience

We offer:

• Stable salary, official employment
• Health insurance
• Hybrid work mode and flexible schedule
• Relocation package offered for candidates from other regions (only for Kazakhstan and Cyprus)
• Access to professional counseling services including psychological, financial, and legal support
• Discount club membership
• Diverse internal training programs
• Partially or fully paid additional training courses
• All necessary work equipment