Data & Business Analyst - Real Estate

SmartRecruiters, Inc.

Milano

On-site

EUR 28,000 - 35,000

Full time

36 hours ago
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Job summary

Colliers in Milano seeks a Data Engineer to build reliable, scalable data solutions within an enterprise data ecosystem. You will work on ingestion pipelines, SQL queries, and Python scripts while engaging with international teams to enable data-driven decisions in real estate.

You bring 2–4 years of experience, PostGIS expertise, and a pragmatic, detail-oriented mindset to support data quality and global collaboration.

Qualifications

  • 2–4 years of experience in Data Engineering or similar roles.
  • Solid knowledge of Python and SQL.
  • Experience with geospatial data and PostGIS.
  • Strong analytical and problem-solving skills.
  • Fluent Italian and good English proficiency; able to collaborate internationally.

Responsibilities

  • Implement and maintain data ingestion pipelines following standards.
  • Write and optimize SQL queries for analytics and geo-spatial use cases.
  • Develop Python scripts for data processing and tools.
  • Support data quality checks and basic monitoring activities.
  • Collaborate with international stakeholders within a shared data framework.

Skills

Python
SQL
Geospatial analysis
Analytical thinking
Team collaboration

Tools

PostGIS
Google Cloud Platform

Job description

  • Compensation: EUR 28,000 - EUR 35,000 - yearly
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 more at corporate.colliers.com.

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
Qualifications
  • 2–4 years of experience in Data Engineering or similar technical roles
  • Solid knowledge of Python and SQL
  • Experience working with geospatial data and tools such as PostGIS
  • Strong analytical and problem-solving skills
  • A reliable, pragmatic, and detail-oriented mindset
  • Ability to work both independently and as part of an international team
  • Fluent Italian (native or C1 level) and good proficiency in English
  • Experience with cloud data platforms (e.g., Google Cloud Platform or similar)
  • Exposure to Real Estate or location-based datasets
  • Curiosity about how data supports business decision-making

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