Staff Software Engineer, Data Platform – LATAM

🕒 March 27

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Luxury Presence

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏠 Real Estate

Real Estate • Marketing

Luxury Presence is a company that specializes in providing real estate professionals with top-tier digital solutions. They offer award-winning real estate website designs and expert marketing solutions aimed at helping agents, teams, and brokerages grow their business and build their brand. Their platform includes tools for IDX home search, property websites, digital CMA, SEO services, content marketing, advertising, and social media management. Trusted by over 20 of the top 100 Wall Street Journal agents, Luxury Presence empowers real estate professionals to attract more business through beautiful and functional digital experiences.

📋 Description

• Own the end-to-end architecture for MLS and property data: streaming and batch pipelines, microservices, storage layers, and APIs • Design and evolve event-driven, Kafka-based data flows that power listing ingestion, enrichment, recommendations, and AI use cases • Drive technical design reviews, set engineering best practices, and make high-quality tradeoffs around reliability, performance, and cost • Design, build, and operate backend services (Python or Java) that expose listing, property, and recommendation data via robust APIs and microservices • Implement scalable data processing with Spark or Flink on EMR (or similar), orchestrated via Airflow and running on Kubernetes where applicable • Champion observability (metrics, tracing, logging) and operational excellence (alerting, runbooks, SLOs, on-call participation) for data and backend services • Build and maintain high-volume, schema-evolving streaming and batch pipelines that ingest and normalize MLS and third-party data • Ensure data quality, lineage, and governance are built into the platform from the start—supporting analytics, AI/ML, and customer-facing features • Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows • Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences • Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance

🎯 Requirements

• 10+ years of professional software engineering experience, including owning production systems end-to-end • Significant experience working with data-intensive or distributed systems at scale (high volume, high availability) • Prior experience in a senior or staff/lead role where you influenced architecture, standards, and technical direction • Strong programming skills in Python or Java, with experience building microservices and APIs (REST/GraphQL) • Hands-on experience with Apache Kafka or similar event/messaging platforms (Kinesis, Pub/Sub, etc.) • Deep experience with Spark or Flink for large-scale data processing, across streaming and batch pipelines (on EMR or similar big-data compute) • Airflow (or equivalent orchestration tools) • Kubernetes for running data/compute workloads • Strong SQL and data modeling skills; solid understanding of ETL/ELT patterns, data warehousing concepts, and performance tuning • Experience building on AWS (preferred) or another major cloud provider, with a good grasp of cost, reliability, and security tradeoffs • Experience building or integrating AI agents into production workflows (e.g., internal tools, support automation, operational triage, or data workflows) • Familiarity with frameworks such as PydanticAI, LangGraph, Claude Code or similar, and how they interact with backend services, vector stores, and LLM APIs • Demonstrated ability to lead technical initiatives across teams, from idea to production (alignment, design, implementation, rollout) • Track record of mentoring other engineers and raising the bar on code quality, testing, and design • Strong communication skills; able to clearly explain complex technical decisions to both engineers and non-technical stakeholders • Customer and product mindset: you care about how the data and services you build improve the end-user and client experience, not just the internals.

🏖️ Benefits

• Equal Opportunity Employer • Professional development opportunities • Flexible work arrangements