ORIL is seeking a highly experienced and autonomous Data Architect / Lead Data Engineer to lead a 2–3 month strategic project focusing on a comprehensive audit and redesign of our mission-critical, AI-driven real estate data platform.
The ideal candidate is a “rockstar” data expert with strong data architecture, data discovery, and data engineering expertise. You will take complete ownership of evaluating our current data layer, determining the target future state (Desired State), and defining a concrete execution roadmap for the engineering team.
About the Project
Our client is a US-based innovator providing a centralized data platform for multi-family real estate. The platform aggregates complex real estate datasets from various external integrations and sources to feed real-time BI analytics (Metabase), power automated operational insights, and drive an intelligent Text-to-SQL AI chatbot.
What are we looking for?
6+ years of experience as a Data Architect, Lead Data Engineer, or Senior Database Engineer;
Proven track record of conducting end-to-end Data Discovery and Audits of complex, multi-source data architectures;
Deep technical expertise in PostgreSQL and relational database design, including advanced query optimization, indexing, schema design, and data modeling;
Hands-on experience with Data Quality, Data Governance, and Data Integrity frameworks (monitoring freshness, volume anomaly, schema drift, semantic metadata validation);
Extensive background in evaluating and architecting ETL/ELT data pipelines and integrations (APIs, web scraping, CDC pipelines);
Strong understanding of structuring metadata, schemas, and semantic layers for AI/LLM integrations (Text-to-SQL) and BI reporting tools (Metabase);
Ability to translate complex business needs into high-level technical vision, concrete architecture blueprints, and resource estimates;
English level: Fluent or Advanced (C1) with strong stakeholder-facing communication skills for direct interactions with US client leadership.
What will you do?
Evaluate the current state of all data collected across multiple integrations — how data is ingested, processed, stored, and presented across the platform.
Analyze schema design, data freshness, bottleneck risks, and overall data health to identify system vulnerabilities and inaccuracies.
Design a clean, scalable, and future-proof target data architecture optimized for fast querying, BI reporting (Metabase), and AI/LLM ingestion (Text-to-SQL).
Build a detailed step-by-step execution plan (Roadmap) specifying required engineering steps, timelines, and resource allocations needed to reach the desired state.
Present audit findings and strategic recommendations directly to the US client leadership and product team.
We Offer:
Project-based contract engagement (2–3 months) with flexible Part-time or Full-time capacity;
Potential for long-term cooperation upon successful project delivery;
Competitive, market-leading compensation;
Full accounting support;
Fully remote work flexibility;
Agile, transparent engineering culture.
Application Process:
Initial Screening Call with Recruiter.
Technical & Architecture Deep Dive with CTO.
Culture Index (CI) Test.
