Data Engineer

Link Logistics; New York (NY); Hybrid; USD 140,000 - 155,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Paid holidays

Paid time off

Job summary

Link Logistics Real Estate in New York is seeking a hybrid ML/Backend Engineer to own the intelligence layer of Link's Analytics Engine. You will design data pipelines, build knowledge graphs, and create backend services that surface insights to investment teams in real time.

You'll blend classical ML, graph-based reasoning, and LLM-native workflows to deliver scalable solutions. The role collaborates with analysts and asset managers to close analytical gaps and improve decision making.

Qualifications

• 4+ years in ML engineering or backend engineering.
• Experience shipping LLM-powered apps in production (RAG, prompts, eval frameworks).
• Strong Python skills and ownership of backend services/APIs.
• Experience with knowledge graphs or graph databases (Neo4j).

Responsibilities

• Design graph-based data structures encoding relationships across markets, assets, tenants, and transactions.
• Build retrieval pipelines (RAG, hybrid search, structured queries) for LLM grounding.
• Develop rule-based and agentic LLM workflows; manage prompts and eval frameworks.
• Create ETL/ELT pipelines for large datasets with clear ownership, cadence and SLA.
• Develop and maintain APIs/services exposing ML outputs with low latency and clean contracts.
• Collaborate with investment and asset management teams to translate needs into scalable analytics.

Skills

ML Engineering

LLM Pipelines

Python

Knowledge Graphs

Data Pipelines

Data Provenance

Tools

Neo4j

Spark

Databricks

Job description

Link Logistics Real Estate (“Link”) is a leading operator of warehouses and business parks, specializing in last-mile logistics real estate. Established by Blackstone in 2019, the company connects consumption, technology, and the supply chain across its portfolio, which spans half a billion square feet. We leverage our scale, proprietary data and insights, and foundational focus on sustainability to drive success for our customers’ businesses and deliver value for our stakeholders. We put our people, customers, and communities first and find ways to make a conscious, positive impact where we live and work. Every day, we work to reinvent and lead our industry forward by thinking bigger and challenging the status quo.

We're hiring a hybrid ML/Backend Engineer to own the intelligence layer of Link's Analytics Engine. This is the connective tissue role: you'll design the pipelines that bring disparate real estate data to life, build the knowledge graphs and retrieval systems that make that data queryable by LLMs, and architect the backend services that surface insights to investment teams in real time.

You won't be handed a spec. You'll talk to investment analysts and asset managers, identify where analytical leverage is lost today, and build systems that close that gap — often combining classical ML, graph-based reasoning, and LLM-native workflows in the same solution.

RESPONSIBILITIES:

• Knowledge Graph & Retrieval — Design graph-based data structures encoding relationships across markets, assets, tenants, and transactions. Build retrieval pipelines (RAG, hybrid search, structured queries) that give LLMs accurate, contextually rich grounding.
• LLM Workflow Automation — Develop rule-based and agentic LLM workflows that automate investment analytical tasks. Own prompt engineering, eval frameworks, and production reliability.
• Data Pipelines — Build ETL/ELT workflows that ingest, normalize, and enrich large-scale internal and third-party datasets (property records, leasing data, macro signals, alt data). Every dataset should have a clear owner, update cadence, and quality SLA.
• Data Trust & Provenance — Build systems that make data trustworthy by design: lineage tracking from source to insight, confidence scoring on derived outputs, and clear attribution so analysts always know where a number came from and how fresh it is. Treat a bad comp or stale signal as a production incident.
• Backend API Layer — Develop and maintain APIs and services that expose ML outputs and structured data to front-end applications. Prioritize low-latency, reliability, and clean contracts with the application team.
• Collaboration — Work directly with investment and asset management teams to understand analytical needs and iterate quickly. Treat analyst trust as a first-class product requirement.

QUALIFICATIONS:

• 4+ years in ML engineering, backend engineering, or a role spanning both
• Hands-on experience shipping LLM-powered applications in production — RAG pipelines, prompt engineering, eval frameworks
• Strong Python skills; comfortable owning backend services and APIs end-to-end
• Experience with knowledge graphs or graph databases (Neo4j or similar)
• Proficiency building data pipelines at scale (Spark, Databricks, or equivalent)
• Deep sensitivity to data provenance — a track record of building systems that create analyst trust, not just claim it

$140,000 - $155,000 represents the presently anticipated base compensation pay range for this position at Link. Actual pay may vary based on various factors, including but not limited to location and experience.

Link provides a variety of benefits to employees, including health insurance coverage, retirement savings plan, paid holidays, paid time off.

The direct compensation and benefits described above are subject to the terms and conditions of any governing plans, policies, practices, agreements, or other materials or documents as in effect from time to time, including but not limited to terms and conditions regarding eligibility.

EEO Statement

The Company is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant, employee, or other covered person based on any legally recognized basis, including, but not limited to: veteran status, uniformed servicemember status, race, color, caste, immigration status, religion, religious creed (including religious dress and grooming practices), sex, gender, gender expression, gender identity, marital status, sexual orientation, pregnancy (including childbirth, lactation or related medical conditions), age, national origin or ancestry, citizenship, physical or mental disability, genetic information (including testing and characteristics), protected leave status, domestic violence victim status, or any other consideration protected by federal, state or local law. We are committed to providing reasonable accommodations, if you need an accommodation to complete the application process, please email [e-mail].