Backend Engineer and Integration Specialist

Summary

Join a pioneering Proptech startup as a Backend Engineer & Integration Specialist to build a scalable, intelligent data infrastructure from the ground up. You will have ownership in shaping backend systems and integration pipelines, working directly with technical leadership and cross-functional teams. This is a remote, full-time position requiring EST work hours. The company offers competitive base salary in USD and additional benefits. The role involves building cloud infrastructure, integrating large data streams, owning the ETL/ELT process, powering search & AI functionalities, and working with various technologies. The company is backed by prominent investors and offers opportunities for growth and development.

Requirements

• 5+ years designing and scaling ETL/ELT pipelines
• Experience building data stacks from scratch or overhauling complex legacy systems
• Strong in Python and SQL (bonus: Java, Scala, or Go)
• Hands-on with: Orchestration : Airflow, Dagster, or Prefect
• Hands-on with: Streaming : Kafka or Kinesis
• Hands-on with: Warehousing : Snowflake or BigQuery
• Hands-on with: IaC & Cloud : AWS, GCP, or Azure
• Experience managing search engines (Elasticsearch) and vector stores (Pinecone, Weaviate)
• Knowledge of ML/AI fundamentals—embeddings, feature stores, model ops
• Passion for clean code, observability, data quality, and security

Responsibilities

• Set up cloud infrastructure (VPCs, IAM, security, IaC via Terraform/Pulumi)
• Define backend architecture, networking standards, and cost-optimized cloud strategies
• Ingest large data streams (REST, XML, EDI APIs) with robust, schema-flexible pipelines
• Build resilient and idempotent data loaders that evolve with external data sources
• Deploy orchestration tools like Airflow , Dagster , or Prefect
• Build and manage dbt pipelines, automated testing, CI/CD workflows, and versioned data repos
• Manage Elasticsearch/OpenSearch clusters and vector databases (Pinecone, Weaviate)
• Enable AI with embeddings, Retrieval-Augmented Generation (RAG), and LLM frameworks like LangChain or LlamaIndex

Preferred Qualifications

• Real-time stream processing (Flink, Apache Beam, Spark)
• Prompt engineering, LLM fine-tuning, or experience with RAG architectures
• Integration of external APIs and third-party data pipelines
• Experience in e-commerce or B2B procurement tech

Benefits

• Annual learning budget for books, courses, and conferences
• Mentorship from startup veterans (ex-Looker, GitHub, Mulesoft)
• Equipment of your choice and remote support