A fast-growing fintech AI start-up company, focused on eliminating fraud and chargebacks in online commerce, is looking for an experienced Senior Data Engineer.
In this Roll, you will build large-scale, cutting-edge data solutions for fraud prevention, with the potential to grow into a technical leadership role.
The company is located in Modi'in, central Israel. Hybrid work model.
Responsibilities
Build and maintain scalable data pipelines and ETL processes.
Design complex data models and optimize data architecture.
Collaborate with teams to deliver high-quality, compliant solutions.
Troubleshoot production issues and implement best practices.
Recommend new technologies to enhance the data infrastructure.
In this Roll, you will build large-scale, cutting-edge data solutions for fraud prevention, with the potential to grow into a technical leadership role.
The company is located in Modi'in, central Israel. Hybrid work model.
Responsibilities
Build and maintain scalable data pipelines and ETL processes.
Design complex data models and optimize data architecture.
Collaborate with teams to deliver high-quality, compliant solutions.
Troubleshoot production issues and implement best practices.
Recommend new technologies to enhance the data infrastructure.
Requirements:
Must Haves:
5+ years in data engineering with strong Python & software engineering skills
Extensive experience with cloud platforms (AWS, GCP, Azure) and cloud-native architectures
Deep knowledge of relational (PostgreSQL) and NoSQL databases
Experience designing and implementing data warehouses and data lakes
Strong understanding of data modeling techniques
Expertise in data manipulation libraries (e.g., Pandas) and big data frameworks
Experience with data validation tools (Pydantic, Great Expectations)
Proficiency in writing and maintaining unit and integration tests (e.g., Pytest)
Nice to Haves / Advantage:
Apache Iceberg, Apache Spark, or modern data stack tools (DBT, DuckDB, Dagster, Airflow, Prefect)
Backend system design: RESTful APIs, microservices, event-driven systems, RabbitMQ, Kafka
Containerization & IaC: Docker, Kubernetes, Terraform
Stream processing: Kafka, Flink
Knowledge of compliance (GDPR, CCPA)
Mentoring or leading small teams
Excellent communication and ability to explain technical concepts clearly
Relevant cloud or data certifications.
Must Haves:
5+ years in data engineering with strong Python & software engineering skills
Extensive experience with cloud platforms (AWS, GCP, Azure) and cloud-native architectures
Deep knowledge of relational (PostgreSQL) and NoSQL databases
Experience designing and implementing data warehouses and data lakes
Strong understanding of data modeling techniques
Expertise in data manipulation libraries (e.g., Pandas) and big data frameworks
Experience with data validation tools (Pydantic, Great Expectations)
Proficiency in writing and maintaining unit and integration tests (e.g., Pytest)
Nice to Haves / Advantage:
Apache Iceberg, Apache Spark, or modern data stack tools (DBT, DuckDB, Dagster, Airflow, Prefect)
Backend system design: RESTful APIs, microservices, event-driven systems, RabbitMQ, Kafka
Containerization & IaC: Docker, Kubernetes, Terraform
Stream processing: Kafka, Flink
Knowledge of compliance (GDPR, CCPA)
Mentoring or leading small teams
Excellent communication and ability to explain technical concepts clearly
Relevant cloud or data certifications.
This position is open to all candidates.
