Zafin
Banking
DataEngineerII
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer II at Zafin. Skills: Data Pipeline Development, Data Modeling, Platform & Infrastructure Management, Data Quality & Observability, Governance & Security, Performance & Cost Optimization, Tooling & Automation. 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”
What You'll Achieve.
drive transformative customer value; accelerate product and pricing innovation; automate deal management and billing; create personalized customer offerings that drive expansion and loyalty; drive sustainable growth; strengthen their market position; define the future of banking centered around customer value; power analytics and product use cases; ensure high standards of data quality, governance, and performance; ensure reliability, scalability, and efficiency; support scalable data consumption; ensure high availability, scalability, and fault tolerance of data systems; ensure data freshness, accuracy, and completeness; improve system performance; managing infrastructure costs; improve engineering productivity
Industry & Context.
optimizing infrastructure; ensuring high standards of data quality, governance, and performance; optimizing queries, partitioning strategies, file formats, and compute resources; managing infrastructure costs
What They're Looking For.
Must Have
5–8 years of experience in data engineering or a related field, programming skills in Python, Scala, or Java, Advanced proficiency in SQL and data modeling concepts, Hands-on experience with Apache Spark, Hands-on experience with Snowflake or similar cloud data warehouses, Hands-on experience with Kafka or other streaming platforms, Hands-on experience with Airflow or similar orchestration tools, Hands-on experience with Kubernetes, Proven experience building both batch and real-time data pipelines, understanding of data quality, observability, and governance frameworks
What You'll Do.
and maintain scalable data pipelines for ingesting
and loading data across batch and real-time (streaming) systems
Integrate data from diverse sources while ensuring reliability
Design and implement optimized data models
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
Ensure high availability
and fault tolerance of data systems
Implement data validation frameworks
and monitoring systems
Establish alerting mechanisms to ensure data freshness
Enforce data governance standards including access controls
Ensure secure handling of sensitive data (PII) aligned with regulatory requirements
partitioning strategies
and compute resources
Continuously improve system performance while managing infrastructure costs
Develop and maintain CI/CD pipelines for data workflows
and automation solutions to improve engineering productivity
How You'll Work.
Team & Collaboration
teamwork
Full Job Description
The world’s top banks use Zafin’s integrated platform to drive transformative customer value. Powered by an innovative AI-powered architecture, Zafin’s platform seamlessly unifies data from across the enterprise to accelerate product and pricing innovation, automate deal management and billing, and create personalized customer offerings that drive expansion and loyalty. Zafin empowers banks to drive sustainable growth, strengthen their market position, and define the future of banking centered around customer value. Role Overview 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. Key Responsibilities Data Pipeline Development 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. Data Modeling 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. Platform & Infrastructure Management Manage and optimize data platforms and infrastructure including Spark, Snowflake, Kafka, Airflow, and Kubernetes. Ensure high availability, scalability, and fault tolerance of data systems. Data Quality & Observability Implement data validation frameworks, automated testing, and monitoring systems. Establish alerting mechanisms to ensure data freshness, accuracy, and completeness. Governance & Security Enforce data governance standards including access controls, data lineage, and compliance
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