Data Integration Engineer (Python)

Description

Backend Engineer & Integration Specialist

📍 Remote | 🕓 Full-time | 🌱 Early-Stage Proptech | 🚀 Greenfield Opportunity
💼 Work Arrangement: Remote (must be able to work EST hours)
💰 Salary: Competitive base salary in USD
🏢 Industry: PropTech / B2B SaaS / Real Estate Technology
🕒 Work Schedule: 40 hours per week

🤝 About Pearl Talent

At Pearl Talent, we work with the top 1% of candidates from around the world and connect them with the best startups in the US and EU. Our clients have raised over $5B and are backed by OpenAI, a16z, and Founders Fund. We place ambitious candidates with founders who value long-term growth, impact, and real ownership.

Why Work with Us?
We’re not just another recruiting firm—we offer retention bonuses (3, 6, 9, 12 months), annual retreats, and deeply aligned opportunities with world-class founders. Many of our hires have even been flown out to work in the US and EU and promoted quickly.

🏢 About the company

Our partner company is a pioneering Proptech startup on a mission to transform how properties are managed and experienced through innovative, AI-powered solutions. As they build their platform from the ground up, we’re looking for a Backend Engineer & Integration Specialist to help us design a scalable, intelligent data infrastructure that powers everything from real-time product discovery to generative AI experiences.

This is a foundational hire —you’ll have true ownership in shaping our backend systems and integration pipelines, working directly with technical leadership and cross-functional teams.

🌟

🏗️

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.

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
- Streaming : Kafka or Kinesis
- Warehousing : Snowflake or BigQuery
- 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.

🎯

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.

🛠

Python • SQL • Airflow • dbt • Kafka • Snowflake/BigQuery • OpenSearch • Pinecone • OpenAI • LangChain • GitHub Actions • End-to-End API Integration

Benefits

💙

Make Your Mark – Be part of our core tech team; every line of code shapes the future of the platform.
Greenfield Innovation – Build an AI-first backend stack without legacy limitations.
Grow With Us – Early-stage startup energy with opportunities to lead and grow fast.

What You’ll Get:

💼 Annual learning budget for books, courses, and conferences
🧠 Mentorship from startup veterans (ex-Looker, GitHub, Mulesoft)
✨ Influence a growing brand in a high-impact role
🌍 Inspiring workspaces in Berlin, New York, and London
🧑‍🚀 Flat hierarchy and founder access
💻 Equipment of your choice and remote support

🚀

Application
Screening
Top-grading Interview
Skills Assessment
Client Interview
Offer
Onboarding

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