Data Engineer, Research & Automation

Our client is an innovative, early-stage US startup operating at the intersection of Artificial Intelligence, 3D Technology, and E-commerce, targeting the home goods market, an industry valued at over USD 400 billion.

The company is developing a next-generation platform that allows people to explore, visualize, and furnish digital versions of their actual homes.

By combining residential data, interactive 3D environments, furniture catalogs, and intelligent design tools, the platform aims to transform how consumers discover, visualize, and purchase home products.

As the company builds its technology and expands its data capabilities, it is looking for a Data Engineer, Research & Automation to help create the data infrastructure powering its digital home experiences.

This is an opportunity to join an early-stage startup, take ownership of complex data challenges, and contribute directly to a product combining AI, 3D technology, and real-world residential information.

About the Role

We are looking for a Data Engineer, Research & Automation who combines strong engineering fundamentals with independent research, data discovery, and automation skills.

You will be responsible for discovering, collecting, organizing, and maintaining the residential information required to build accurate digital representations of real homes.

Unlike traditional data engineering roles focused primarily on internal analytics, this position requires hands-on external data research, web scraping, API integrations, data extraction, and automated collection pipelines.

You will investigate new data sources, evaluate their reliability and coverage, identify missing information, and develop scalable solutions to transform fragmented external data into structured, usable datasets.

The ideal candidate is a resourceful engineer who enjoys solving ambiguous problems, exploring unconventional data sources, and building reliable automation systems with minimal supervision.

Key Responsibilities

Data Research & Source Discovery

• Research and evaluate new sources of residential information, including buildings, individual units, property listings, floor plans, photographs, and related records.
• Assess data sources based on coverage, accuracy, reliability, freshness, and usage constraints.
• Identify missing or incomplete information and develop creative approaches to improve data coverage.
• Continuously improve extraction methods and data quality across existing sources.

Data Extraction & Automation

• Design, develop, and maintain web scraping systems, web indexing processes, browser automation, and public API integrations.
• Build scalable ingestion workflows to collect and process large public datasets.
• Develop automated processes for data collection, enrichment, transformation, and updates.
• Minimize manual intervention through reliable automation, error handling, retries, and recovery mechanisms.
• Monitor and improve the performance, reliability, and efficiency of data extraction pipelines.

Data Engineering & Architecture

• Design and maintain databases and information architectures connecting buildings, residential units, floor plans, images, and original source records.
• Transform unstructured and inconsistent external information into clean, structured, and usable datasets.
• Implement data normalization, record matching, deduplication, and reconciliation processes.
• Resolve conflicting information while preserving data provenance, source evidence, and freshness.
• Develop validation mechanisms to identify incorrect matches, missing information, and data inconsistencies.
• Deliver reliable datasets and supporting evidence to the engineering team responsible for building digital home models.

Engineering Ownership

• Take end-to-end ownership of data discovery and automation initiatives, from identifying problems to delivering production-ready solutions.
• Collaborate with engineering and product teams to define data requirements and priorities.
• Proactively investigate data gaps, propose technical solutions, and improve existing workflows.
• Ensure data pipelines are maintainable, observable, and capable of operating reliably at scale.

Required Qualifications

Data Engineering & Automation

• Approximately 3–8 years of professional engineering experience, with demonstrated capability in data extraction, automation, and database development.
• Strong hands-on experience with Python and SQL, or equivalent technologies.
• Practical experience building web scraping systems, browser automation, or automated data collection workflows.
• Experience integrating external APIs and processing large or complex datasets.
• Solid understanding of relational databases, data modeling, and information architecture.
• Proven ability to transform messy, incomplete, or inconsistent external data into structured datasets.
• Experience building repeatable and reliable automation pipelines.

Data Research & Quality

• Strong research skills and the ability to independently discover and evaluate new data sources.
• Experience assessing data accuracy, completeness, coverage, and reliability.
• Understanding of data deduplication, entity matching, record reconciliation, and data validation.
• Ability to identify and manage risks associated with incorrect record matching or conflicting information.
• Awareness of data usage restrictions and responsible data collection practices.

AI-Assisted Development

• Hands-on experience using AI coding agents and AI-powered development tools.
• Ability to leverage AI for technical research, implementation, debugging, testing, and documentation.
• Strong engineering judgment when reviewing, validating, and maintaining AI-generated code.
• Comfortable working in an AI-first engineering environment where productivity, quality, and reliability are equally important.

Professional Skills

• Strong problem-solving abilities and a resourceful, research-oriented mindset.
• High level of autonomy and accountability for technical deliverables.
• Ability to work effectively in ambiguous, fast-paced startup environments.
• Curiosity, initiative, and willingness to explore new tools and approaches.
• Strong communication and collaboration skills.
• Fluent professional English, both written and spoken.
• Availability to work with significant overlap with New York business hours.

Relevant Tech Stack

Experience with the following technologies and practices is particularly relevant. Equivalent tools and languages are also welcome.

• Programming: Python, SQL
• Data Extraction: Web Scraping, Web Indexing, Public APIs
• Browser Automation: Browser Automation Frameworks
• Data Engineering: ETL/ELT, Data Ingestion, Data Transformation
• Databases: Relational Databases, Data Modeling
• Data Quality: Deduplication, Entity Resolution, Validation, Provenance
• Workflow Automation: Data Orchestration, Scheduled Pipelines, Retries, Recovery
• AI Development: AI Coding Agents, AI-Assisted Engineering Tools

Nice to Have

• Experience working with real estate, residential, property listing, or geographic datasets.
• Background building large-scale web indexing or public-data collection systems.
• Experience with entity resolution, record linkage, or complex data reconciliation.
• Familiarity with data orchestration frameworks and automated data quality monitoring.
• Contributions to open-source projects involving data extraction, scraping, or automation.
• Personal projects or hackathon experience demonstrating creative approaches to data collection.
• Experience working in early-stage startups or small engineering teams.
• Interest in AI, 3D technology, digital twins, or interactive e-commerce.

How We Work

We are an AI-first team that actively embraces AI coding agents and modern development tools throughout the software development lifecycle.

We expect engineers to demonstrate how they already use AI to accelerate research, development, debugging, testing, and documentation while remaining fully accountable for the quality and reliability of their work.

We value useful output, engineering quality, independent execution, and adaptability over expertise in any single programming language or framework.

You will be encouraged to investigate problems independently, identify opportunities, propose solutions, and execute without waiting for detailed instructions.

Our environment rewards curiosity, initiative, practical problem-solving, and a strong sense of ownership.

Why Join Us?

• Build an Innovative Product: Contribute to a platform combining AI, 3D technology, residential data, and interactive e-commerce.
• Early-Stage Impact: Join a startup where your work will directly influence product capabilities and technical direction.
• High Ownership: Lead data research and automation initiatives from discovery to implementation.
• Complex Engineering Challenges: Solve real-world problems involving fragmented datasets, source discovery, entity matching, and large-scale automation.
• AI-First Culture: Work in an environment that encourages practical AI adoption and modern engineering workflows.
• Long-Term Opportunity: Help develop the data foundation of a growing technology platform.

Compensation & Working Arrangement

• Annual Compensation: USD 78,000–96,000.
• Employment Type: Full-time, long-term.
• Working Hours: As much overlap as practical with New York business hours (ET).
• English: Fluent professional proficiency.

If you are a hands-on Data Engineer who enjoys discovering valuable data sources, building intelligent automation systems, and turning complex external information into reliable datasets, we would love to hear from you. Join an ambitious early-stage startup and help build the data infrastructure behind the next generation of digital home experiences.