Backend Engineer (Data & Integrations) - A291 job opportunity at Pearl Talent.

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Date2026-02-10T15:06:29.109Z bot
Pearl Talent Backend Engineer (Data & Integrations) - A291
Experience: 5-years
Pattern: Full-time
Country:
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degreeHigh School (S.S.C.E)
loacation Costa del Este, Argentina
loacation Costa del Este....Argentina

Industry PropTech / SaaS Work Arrangement Full-time • Remote Job Type Full-time Work Schedule EST hours Locations: LATAM preferred • Open to any region About Pearl Talent Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They’re looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we’ve hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US. Hear why we exist, what we believe in, and who we’re building for: WATCH HERE Why Work with Us? At Pearl, we’re not just another recruiting firm—we connect you with exceptional opportunities to work alongside visionary US and EU founders. Our focus is on placing you in roles where you can grow, be challenged, and build long-term, meaningful careers. About the Company Our client is a fast-growing, venture-backed technology company operating in the property and real estate software space. They are building a modern, cloud-native platform that reimagines how property operations are managed by combining large-scale data infrastructure, intelligent search, and AI-powered workflows. This is a greenfield environment where early technical decisions shape the long-term platform architecture, performance, and scalability. Role Overview The Backend Engineer & Integration Specialist is a foundational technical hire responsible for designing and scaling the company’s backend systems, data infrastructure, and external integrations from the ground up. This role sits at the intersection of backend engineering, data pipelines, platform infrastructure, and AI enablement. You will build secure, scalable systems that ingest and process large volumes of external data, power real-time discovery experiences, and support production-grade AI and generative features. The role is highly autonomous, deeply technical, and ideal for an engineer who thrives in zero-to-one environments, enjoys architectural ownership, and wants long-term influence on platform direction. Your Impact You will architect and launch backend and data systems that serve as the foundation of the company’s core product. You will enable reliable ingestion and processing of large-scale external data sources, ensuring high availability and data quality. You will help unlock intelligent search, discovery, and AI-driven features through scalable indexing and vector systems. You will improve engineering efficiency, reliability, and cost control through strong infrastructure, observability, and automation practices. You will directly influence the company’s ability to scale product features, onboard data partners, and deliver AI-powered user experiences. Core Responsibilities Backend & Infrastructure Foundations – 25% Architect and provision secure cloud environments, including networking, IAM, and security best practices. Implement Infrastructure-as-Code using tools such as Terraform or Pulumi. Establish standards for secrets management, cost optimization, and observability. Design scalable backend services to support core product functionality. Data Ingestion & External Integrations – 25% Design and build robust integrations with third-party APIs and external systems. Develop resilient, idempotent ingestion pipelines capable of handling large-scale data volumes. Implement schema management, data validation, and fault-tolerant ingestion workflows. Maintain reliable data synchronization across multiple sources. Pipeline & Platform Engineering – 20% Build and maintain ETL/ELT pipelines using modern orchestration tools. Implement transformation workflows using dbt and manage CI/CD pipelines for backend and data services. Develop automated testing, monitoring, and alerting to ensure data quality and system reliability. Search, Indexing & Vector Systems – 15% Provision and scale distributed search platforms such as Elasticsearch or OpenSearch. Deploy and manage vector databases, including backups, scaling, and upgrades. Optimize indexing strategies for fast, intelligent retrieval across large datasets. AI & Generative Enablement – 15% Build backend pipelines for generating and managing embeddings using modern ML models. Support Retrieval-Augmented Generation (RAG) systems using industry-standard frameworks. Collaborate with product and AI teams to enable scalable, production-ready AI features. Must-Haves (Required) 5+ years of experience building and scaling backend systems and data pipelines in production environments. Proven experience designing greenfield platforms or modernizing complex systems. Strong proficiency in Python and SQL, with working knowledge of at least one additional backend language. Hands-on experience with orchestration tools and data transformation frameworks. Experience with streaming or messaging platforms such as Kafka or similar systems. Experience working with cloud data warehouses like Snowflake or BigQuery. Strong experience managing distributed search systems and vector databases. Practical exposure to ML and AI concepts, including embeddings and model-serving workflows. Deep experience with at least one major cloud provider and Infrastructure-as-Code practices. Strong written and verbal English communication skills and cross-functional collaboration ability. Nice-to-Haves (Preferred) Experience with real-time stream processing frameworks. Prior work with RAG architectures, prompt engineering, or LLM fine-tuning. Background in data ingestion-heavy or API-centric platforms. Experience in PropTech, B2B SaaS, or e-commerce environments. Tools Proficiency Must-Haves (Required) Python, SQL, Airflow, Dagster, Prefect, dbt, Kafka, Snowflake, BigQuery, Elasticsearch, OpenSearch, Pinecone, Weaviate, AWS, GCP, Azure, Terraform, Pulumi, GitHub Actions Nice-to-Haves (Preferred) LangChain, LlamaIndex, OpenAI, Hugging Face, Apache Flink, Apache Beam, Spark Structured Streaming

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