Staff Software Engineer, Data Platform

🕒 vor 5 Monaten

🇺🇸 Vereinigte Staaten – Remote

💵 $200.000 - $230.000 / Jahr

⏰ Vollzeit

🔴 Experte

🧑‍💻 Full-Stack-Entwickler

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

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Luxury Presence

WebsiteLinkedInAlle Stellen

201 - 500 Mitarbeiter

🏠 Immobilien

Real Estate • Marketing

Luxury Presence ist ein Unternehmen, das sich auf die Bereitstellung erstklassiger digitaler Lösungen für Immobilienprofis spezialisiert hat. Sie bieten preisgekrönte Immobilien-Website-Designs und erstklassige Marketinglösungen, die darauf abzielen, Agenten, Teams und Maklerhäusern zu helfen, ihr Geschäft auszubauen und ihre Marke zu stärken. Ihre Plattform umfasst Tools für die Immobilien-Suchmaschinen-Optimierung (IDX), Immobilien-Websites, digitale Immobilienbewertungen (CMA), SEO-Dienstleistungen, Content-Marketing, Werbung und Social-Media-Management. Vertraut von über 20 der Top 100 Wall Street Journal-Agenten, ermöglicht Luxury Presence Immobilienprofis, durch ansprechende und funktionale digitale Erlebnisse mehr Geschäft zu generieren.

Beschreibung

• 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 • Partner with analytics engineering and data science to make data discoverable and usable (e.g., semantic layers, documentation, self-service tooling) • Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows • Work with frameworks such as PydanticAI, LangChain, or similar to integrate LLM-based agents into our data and service architecture • Help define and implement evaluation, logging, and feedback loops so these agents and data-driven products continuously improve • Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences • Translate ambiguous business and customer problems into clear technical strategies and phased delivery plans • Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance

🎯 Anforderungen

• 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 • Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems • 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 • Experience with any of: • ◦ Iceberg, Hive, or other table formats/data lake technologies • ◦ Snowflake, Athena, Redshift, or other cloud data warehouses • ◦ dbt or similar transformation frameworks • ◦ Data quality / observability tools (e.g., Great Expectations, Monte Carlo, Datafold) • ◦ Vector databases / retrieval (e.g., LanceDB, Pinecone, Elasticsearch/OpenSearch) • Background in real estate, marketplaces, or other domains where data quality and freshness are highly visible to customers • Prior experience in a startup or high-growth environment where you’ve built or significantly evolved a data platform