Senior Data Engineer - GraphDB Expertise at Chargeflow

Modiin-Maccabim-Reut, Center District, Israel -

Full Time

Start Date

Immediate

Expiry Date

04 Apr, 26

Salary

0.0

Posted On

04 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, GraphDB, AWS, GCP, Azure, Relational Databases, NoSQL Databases, Data Warehousing, Data Lakes, Data Modeling, Data Manipulation, Big Data Processing, Data Validation, Unit Testing, Integration Testing, Apache Spark, Containerization

Industry

Financial Services

Description

Welcome to Chargeflow Chargeflow is at the forefront of fintech + AI innovation, backed by leading venture capital firms. Our mission is to build a fraud-free global commerce ecosystem by leveraging the newest technology, freeing online businesses to focus on their core ideas and growth. We are building the future, and we need you to help shape it. Who We're Looking For - The Dream Maker We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud. Your Arena Design, develop, and maintain scalable, robust data pipelines and ETL processes Architect and implement complex data models across various storage solutions Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions Ensure data quality, consistency, security, and compliance across all data systems Play a key role in defining and implementing data strategies that drive business value Contribute to the continuous improvement of our data architecture and processes Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges Participate in and sometimes lead code reviews to maintain high coding standards Troubleshoot and resolve complex data-related issues in production environments Evaluate and recommend new technologies and methodologies to improve our data infrastructure Requirements What It Takes - Must haves: 5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must Extensive experience with GraphDB - MUST Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must Designing and implementing data warehouses and data lakes - Must Strong understanding of data modeling techniques - Must Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must Experience with data validation tools such as Pydantic & Great Expectations - Must Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must Nice-to-Haves Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage Understanding of compliance requirements (e.g., GDPR, CCPA) - Advantage Experience mentoring junior engineers or leading small project teams Excellent communication skills with the ability to explain complex technical concepts to various audiences Demonstrated ability to work independently and lead technical initiatives Relevant certifications in cloud platforms or data technologies Our Story Chargeflow is a leading force in fintech innovation, tackling the pervasive issue of chargeback fraud that undermines online businesses. Born from a deep passion for technology and a commitment to excel in eCommerce and fintech, we've developed an AI-driven solution aimed at combating the frustrations of credit card disputes. Our diverse expertise in fintech, eCommerce, and technology positions us as a beacon for merchants facing unjust chargebacks, supported by a unique success-based approach. Backed by $49M led by Viola Growth, OpenView, Sequoia Capital and other top tier global investors, Chargeflow has embarked on a product-led growth journey. Today, we represent a tight-knit community of passionate individuals and entrepreneurs, united in our mission to revolutionize eCommerce and fight against chargeback fraud, marking us as pioneers in protecting online business revenues.

Responsibilities

The Senior Data Engineer will design, develop, and maintain scalable data pipelines and ETL processes while collaborating with various teams to deliver high-quality data solutions. They will also ensure data quality and compliance, contribute to data architecture improvements, and troubleshoot complex data issues.