Zafin
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Software Development · 501 to 1000 Employees · Toronto, Canada
Zafin is a global leader in banking product and pricing solutions, assisting banks in unlocking untapped capabilities within their existing data. We are on a mission to empower banks to achieve increased revenue, enhanced profitability, and elevated customer experiences. Since our launch in 2002, we have consistently invested 25% of our revenues in developing and upgrading our products and their capabilities.
Hiring: Engineering
What employees say
+ Good for learning new technologies and to skill up Good workspace and facilities Safe workplace
− Growth and pay scale is limited. Favourtism is generally seen in this company
More reviews on the company profile.
Interview experience · Cloud Support Engineer
Ghosted on first interview and didn't give any response until next day and then rescheduled it for another day and on that day the panel joined 20 mins late and asked me if u could reschedule and then did the interview a
Average difficulty · India · 29 reports
More interview insightsJob description
Overview
Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered.
Responsibilities
- We are seeking a highly skilled Data Engineer II to design, build, and scale robust data platforms that power analytics and product use cases. This role requires strong ownership in developing data pipelines, optimizing infrastructure, and ensuring high standards of data quality, governance, and performance. The ideal candidate brings deep hands-on
- experience with modern data technologies and thrives in a fast-paced, product-driven environment.
- Design, build, and maintain scalable data pipelines for ingesting, transforming, and loading data across batch and real-time (streaming) systems.
- Integrate data from diverse sources while ensuring reliability, scalability, and efficiency.
- Design and implement optimized data models, warehouse schemas, and tables for analytics and reporting.
- Apply best practices in data architecture to support scalable data consumption.
- Manage and optimize data platforms and infrastructure including Spark, Snowflake, Kafka, Airflow, and Kubernetes.
- Ensure high availability, scalability, and fault tolerance of data systems.
- Implement data validation frameworks, automated testing, and monitoring systems.
- Establish alerting mechanisms to ensure data freshness, accuracy, and completeness.
- Enforce data governance standards including access controls, data lineage, and compliance.
- Ensure secure handling of sensitive data (PII) aligned with regulatory requirements.
- Optimize queries, partitioning strategies, file formats, and compute resources.
- Continuously improve system performance while managing infrastructure costs.
- Develop and maintain CI/CD pipelines for data workflows.
- Build internal tools, reusable frameworks, and automation solutions to improve engineering productivity.
Qualifications
- 5–8 years of experience in data engineering or a related field.
- Strong programming skills in Python, Scala, or Java.
- Advanced proficiency in SQL and data modeling concepts.
- Hands-on experience with:
- Apache Spark (distributed data processing)
- Snowflake or similar cloud data warehouses
- Kafka or other streaming platforms
- Airflow or similar orchestration tools
- Kubernetes (container orchestration)
- Proven experience building both batch and real-time data pipelines.
- Strong understanding of data quality, observability, and governance frameworks.
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