Software Engineering, Principal

Hace 10 horas

buenos aires, Argentina Medallia Jornada completa

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Overview

Medallia is the pioneer and market leader in Experience Management. Our award-winning SaaS platform, Medallia Experience Cloud, leads the market in the management of experiences, insights, and actions for candidates, customers, employees, patients, and residents alike.

We believe that every experience is a memory that can last a lifetime. Experiences shape the way people feel about a company. And they greatly influence how likely people are to advocate, contribute, and stay. At Medallia, we are committed to creating a world where organizations are loved by their customers and their employees.

We empower exceptional people to create extraordinary experiences together.

Bring your whole self.

The Role

At Medallia, we help the world’s leading organizations capture experience signals and transform them into real-time intelligence and action. As AI-native systems evolve, traditional transactional architectures are no longer enough. The future belongs to platforms that can continuously sense, interpret, and react to live operational and behavioral signals in real time.

We are building the next generation of intelligent, event-driven platforms and are looking for a Principal Data & Event Intelligence Engineer to architect the real-time nervous system powering AI-driven decisioning, automation, and personalization across Medallia.

Mission

Transform the enterprise from static CRUD and transactional systems into a real-time intelligence platform. This role is responsible for building the foundational event and streaming infrastructure that powers operational AI, behavioral intelligence, autonomous workflows, and adaptive customer experiences. You will design the systems that continuously ingest, process, enrich, and activate enterprise signals at scale — including both operational (transactional) and analytical (OLAP) data paths, and the vector-based retrieval layers that ground AI systems — enabling AI systems and products to operate with real-time awareness and responsiveness.

Responsibilities

Event-Driven Platform Architecture

Architect and scale enterprise-wide event-driven systems powering real-time intelligence and AI workflows Design highly resilient streaming architectures supporting billions of events and low-latency processing, using Flink for stateful stream processing, windowing, and complex event processing Build foundational event ingestion, routing, enrichment, and distribution frameworks, including bidirectional streaming in and out of the data platform (source connectors, CDC pipelines, and downstream activation/egress into operational and analytical systems) Define event contracts, schemas, governance standards, and interoperability patterns across platforms Drive the transition from request/response transactional systems toward reactive, event-native architectures

Real-Time Signal & Behavioral Intelligence

Build real-time customer, employee, product, and operational signal pipelines Develop behavioral intelligence systems that continuously analyze activity streams and contextual signals Create streaming analytics capabilities enabling dynamic decisioning, anomaly detection, and adaptive workflows Build operational AI feedback loops that continuously improve AI systems using live interaction data Enable AI systems to react to changing enterprise state with minimal latency

Data Infrastructure & Temporal Systems

Design feature stores, event stores, and temporal data architectures optimized for AI and machine learning workloads Build systems supporting time-aware reasoning, sequence analysis, sessionization, and historical replay Architect low-latency operational data stores using YugabyteDB for distributed, horizontally scalable, strongly consistent transactional workloads Design and operate high-performance OLAP serving layers using StarRocks for real-time analytical queries over streaming and batch data at scale Design and evolve vector store architecture (indexing strategies, hybrid search, embedding lifecycle management) to support semantic search, RAG, and AI grounding use cases across the platform Implement cross-platform telemetry normalization and unified signal modeling Develop scalable infrastructure for high-throughput event storage, retention, replay, and observability Optimize data freshness, consistency, throughput, and processing efficiency at scale

Personalization & Agent Activation

Build real-time personalization infrastructure powering adaptive user experiences and intelligent workflows Design agent-trigger systems enabling autonomous AI actions based on live signals and behavioral conditions Create context propagation and streaming enrichment system

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