As an IC5 Senior Staff Engineer, you will architect and deliver large‑scale distributed platform components, lead complex technical initiatives, and define engineering best practices.
Responsibilities
Architect, design, and build high‑performance distributed systems and platform components.
Build distributed systems data ingestion solutions with strong emphasis on scalability, quality, and operational excellence.
Deliver high‑quality, clean, modular, and reusable code while enforcing engineering best practices (code reviews, unit testing, automation, design reviews).
Build foundational libraries, frameworks, and tools focused on modularity, extensibility, configurability, and maintainability.
Collaborate across engineering teams to refine requirements and deliver end‑to‑end solutions.
Análisis de aplicaciones: Generación de Historias de Usuario Funcionales y Técnicas. Identificación de Casos de Uso
Diseño de la Interoperabilidad: Definir los patrones de integración para permitir que sistemas dispares (legados, REST APIs, bases de datos) publiquen o consuman datos en Kafka
Gestión de Datos: Diseño del modo de datos, así como de la estrategía de transformación y mapeo de datos entre sistemas, garantizando la interoperabilidad semántica
Desarrollo de Producers/Consumers: Implementar aplicaciones (APIs, microservicios) que utilicen las APIs de Java o lenguajes compatibles para escribir y leer datos de los topics
Implementación de ETL en Tiempo Real: Configurar pipelines de procesamiento de datos utilizando Kafka Connect para mover información de manera continua entre sistemas y plataformas como S3, MongoDB, ElasticSearch, etc.
Design, build, and maintain robust data pipelines and data lake architecture for both batch and real-time streaming use cases, including high-volume, low-latency data processing
Responsibilities
Design, build, and maintain robust data pipelines and data lake architecture for both batch and real-time streaming use cases, including high-volume, low-latency data processing
Improve observability, alerting, and SLOs across data systems so pipelines are easier to monitor and issues are caught early
Optimize ETL/ELT workflows for performance, scalability, and fault tolerance
Develop dbt workflows to onboard Evaluation Partners and create end of day reporting for partner analysis
Build and support event-driven architectures and scalable platform components
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field
A hands-on role to design, build, and operate real-time data products on an enterprise data platform, taking ownership from event ingestion and stream processing to the APIs used by consumers.
Responsibilities
Design and deliver end-to-end streaming data products using Apache Flink, Apache Kafka, and event-driven architectures.
Develop stateful stream-processing applications, including windowing, event-time handling, watermarks, checkpointing, and exactly-once processing guarantees.
Build and maintain resilient ingestion, transformation, and delivery pipelines for real-time and batch workloads.
Manage Kafka topics, partitioning, consumer groups, schemas, and schema evolution.
Design and develop REST APIs, streaming interfaces, and microservices with clear contracts, versioning, authentication, and rate limiting.
Lead the design, build, and optimization of data pipelines for Wise’s Finance Squad, ensuring scalable, accurate, and compliant financial data processing.
Compensation
Starting salary: £111k - £145k + RSUs
Responsibilities
Design, build, and optimize end-to-end data pipelines on Trino + Iceberg Lakehouse stack
Own extraction, cleaning, and modeling layers following Medallion Architecture
Implement stream processing with Kafka to maintain data freshness SLAs
Embed automated reconciliation checks for data quality and compliance
Collaborate with finance controllers, analysts, product and engineering teams
We are seeking a Senior Integration Engineer to design, develop, and maintain robust data integration solutions. You will focus heavily on real-time data streaming via Apache Kafka and cloud-native ETL pipeline orchestration using AWS Glue. You will collaborate across engineering and product teams to ensure seamless data flows across our entire ecosystem.
Responsibilities
Build and optimize scalable streaming solutions using Apache Kafka, Kafka Connect, and Kafka Streams.
Architect and manage ETL/ELT pipelines and the Data Catalog using AWS Glue to move data efficiently into lakes and warehouses.
Connect cloud applications and third-party services using AWS Lambda, S3, API Gateway, SQS, SNS, and EventBridge.
Champion event-driven architecture and microservices principles.
Mentor junior engineers and provide technical leadership.
The Lead Software Engineer is the highest individual contributor technical role responsible for setting technical vision, driving architectural excellence, and solving the most complex technical challenges for Visa's Acceptance Solutions platform, focusing on transaction processing platform.
Compensation
For roles located in the US, the estimated salary range for this position is $174,400.00 to $ 279,100.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.
Responsibilities
Design and build scalable, secure, and resilient software systems that support Visa’s Acceptance Solutions platform and global transaction processing capabilities.
Set technical direction and influence architectural standards for distributed systems, platform reliability, scalability, security, and reusability.
Lead the development of mission‑critical transaction processing solutions that support high‑volume payment flows, event‑driven processing, and real‑time data movement.
Collaborate with product, architecture, security, operations, and engineering teams to create design artifacts and deliver best‑in‑class software solutions.
Solve complex technical challenges across cloud‑native platforms, distributed architecture, event streaming, API security, and payment lifecycle management.
Sr. Data EngineerNewNinjaTrader · Remote, US