Data & Business Analyst - Real Estate
Pubblicato il 19-10-2026 - Colliers in Venezia
Company Description Colliers (NASDAQ, TSX: CIGI) is a global diversified professional services and investment management company operating through three industry-leading businesses: Commercial Real Estate, Engineering and Investment Management. With greater than a 30-year track record of consistent growth and strong recurring cash flows, we scale complementary, high-value businesses that provide essential services across the full asset lifecycle. Our unique partnership philosophy empowers exceptional leaders, preserves our entrepreneurial culture, and ensures meaningful inside ownership – driving strong alignment and sustained value creation for our shareholders. With $6 billion in annual revenues, 28,000 professionals, and $110 billion in assets under management, Colliers is committed to accelerating the success of our clients, investors, and people worldwide. Learn .
Job Description You are a Data Engineer with a passion for hands‑on development and a strong interest in building reliable, scalable data solutions. You enjoy working in structured environments, following clear standards,
and contributing to real‑world, operational systems.
You bring a pragmatic and detail‑oriented mindset, combined with solid technical foundations in data engineering. You are comfortable collaborating with international teams and are motivated to grow your expertise within an enterprise‑grade data ecosystem.
You are curious, proactive, and eager to understand how data supports business decisions, particularly within a complex and evolving industry like real estate.
Your Activities
- Implementing and maintaining data ingestion pipelines, following company standards
- Writing and optimizing SQL queries, including analytical and geo spatial use cases
- Developing Python scripts for data processing, transformations and data acquisition tools
- Supporting data quality checks and basic monitoring activities
- Collaborating with international stakeholders within a shared data framework
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