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Staff Data Engineer - Governance

Blip Global
CompanyBlip Global
CategoryEngineering
LocationRemote - Brazil
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted2 Oct 2025
Last verified3 Aug 2026
SourceEmployer career page (greenhouse)
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Description
About the Role At Blip, data is more than a byproduct, it's a strategic asset. Our Data Platform powers everything from internal decision-making to the next generation of AI-driven experiences. We're now looking for a Sr. Staff Data/Platform Engineer to play a foundational role in scaling and evolving this platform. This role is ideal for someone who is passionate about solving deep engineering challenges, working across large-scale distributed systems, and translating real-time data into meaningful intelligence across the company. Your Mission You’ll be the technical backbone of our Data and Platform Engineering team, owning critical platform decisions, mentoring engineers, and designing future-proof, low-latency, high-throughput systems that power analytics, machine learning, and real-time business logic. As a senior individual contributor, you’ll work side-by-side with product, infrastructure, and AI teams, helping shape Blip’s data foundation for years to come. Key Responsibilities Platform Engineering & Distributed Systems Design, implement, and optimize distributed data systems using technologies like Kafka, Flink, Spark, and Delta Lake , ensuring scalability, fault tolerance, and high performance across streaming and batch workloads. Streaming & Real-time Data Pipelines Build and maintain low-latency, high-throughput pipelines capable of handling billions of events per day, powering real-time dashboards, ML feature stores, and intelligent products. Data Architecture & Systems Design Translate business requirements into robust, scalable architectural patterns, integrating best practices across data modeling, orchestration, data governance, and observability . Engineering Excellence & Code Quality Write high-quality, maintainable code and establish patterns that raise the engineering bar. Collaborate in code reviews and mentor other engineers in software craftsmanship. AI Infrastructure & Decision Systems Help bridge traditional machine learning workloads with modern AI-based decision systems. Support the evolution of our ML pipelines into agent-based or model-context protocol (MCP)-enabled workflows. Collaboration & Leadership Work cross-functionally with Product, AI, and Software Engineering teams to drive platform adoption and unlock new capabilities. Act as a technical leader and sounding board on system evolution and architecture choices. What We're Looking For Experience 8+ years in Data Engineering, Platform Engineering, or Software Engineering roles. Demonstrated expertise building and scaling distributed systems and data platforms . Deep hands-on experience with Apache Kafka , Apache Flink , Apache Spark , Delta Lake , or similar technologies. Strong knowledge of streaming architectures , real-time data processing, and event-driven systems. Technical Foundations Solid foundation in software engineering : design patterns, testing, CI/CD, versioning, clean code. Proficiency in modern languages such as Scala, Java, or Python . Expertise in SQL , data modeling , and performance tuning for analytical and transactional workloads. Bonus Points Experience implementing or working with Model Context Protocol (MCP) or modern AI infrastructure paradigms. Familiarity with ML Ops , feature stores, and model deployment frameworks. Knowledge of data governance principles, observability stacks, and RBAC/RLS at scale.   *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="86c09730-cbf8-4f4e-9fce-716955ee5afb" data-testid="conversation-turn-2" data-scroll-anchor="true" data-turn="assistant"> Perks and Benefits Your Day-to-Day Experience 🕘 Flexible Hours: Enjoy autonomy to organize your routine with balance and responsibility. 🏠 Flexible Work Models: Remote, hybrid, or on-site ��
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