SUMMARY

The Data Platform team at Pismo is responsible for integrating data produced by Pismo’s Banking as a Service/Payments platform with its clients, whether through batch processing (files) or near real-time (events). With a robust, low-latency, and 100% cloud-based architecture, the team excels in technology and fosters a strong culture of collaboration, partnership, and data-driven decision making for platform development and project prioritisation

MINIMUM QUALIFICATIONS

Technical Skills:

• 4+ Years experience as a Data Engineer
• Python / Golang Experience
• Architectural Design experience
• Strong experience of AWS Services (eg Lambda, Kinesis, SQS, Firehose, and S3)
• Stream Processing and Delivery: Kinesis, Confluent Cloud, Amazon SNS, SQS and Event Bridge.
• Monitoring Tools: Grafana and Cloudwatch. (Logs / tracing / spans / monitor / alerts / dashboards)
• SQL experience
• Git / Github exposure

DESIRABLE QUALIFICATIONS

• CI/CD Experience
• Able to communicate in Portuguese
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  Pismo is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Pismo does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. Pismo also strives for a healthy and safe workplace and strictly prohibits harassment of any kind

• Serve as a senior technical contributor on Pismo’s data stack, leading the design and development of robust, scalable data pipelines using modern Big Data frameworks.
• Drive continuous improvement in platform performance, reliability, and cost-effectiveness, proactively identifying opportunities for innovation.
• Take ownership of production operations and monitoring (file- and event-based systems), ensuring adherence to SLAs and applying best practices for observability and resilience.
• Collaborate with cross-functional teams to architect, build, and evolve high-complexity data features, reducing technical debt and championing engineering excellence.
• Provide mentorship to peers through code reviews, feedback, and support, fostering an environment of knowledge sharing and professional development.
• Participate in on-call rotations, promptly addressing and resolving production incidents, while proactively implementing preventative measures.
• Build and optimize ETL/ELT processes to handle large-scale data, leveraging advanced data processing and distributed systems techniques.
• Maintain rigorous data governance and platform standards, working closely with data stakeholders to ensure consistent, high-quality data assets.
• Introduce and adopt new technologies, tools, or techniques that accelerate development cycles, improve performance, and reduce costs.