Senior Data Platform Engineer

DESCRIPTION

Our story began three years ago when Skyline AI was acquired by JLL (NYSE: JLL), a global leader in professional services and investment management, specializing in commercial real estate. We are now part of a Fortune 500 company, with operations in over 80 countries, a workforce of over 100,000 individuals, and substantial capital to invest in innovative tech solutions.

We’re proud to be part of JLL Technologies, the strategic business group dedicated to utilizing state-of-the-art technology to enhance the value and liquidity of buildings worldwide, with the overarching mission of revolutionizing the commercial real estate industry.

At our Tel Aviv office, you’ll join a team of 40 passionate people across data, software, product, design, and operations. When we’re not building cool products, you’ll find us lifting weights in the gym, jamming in the music room, or enjoying top-notch coffee from our barista machine.

We value strong relationships and connections, coming together to the office to collaborate and share lunch, while also enjoying the flexibility of a truly Hybrid work model.

REQUIREMENTS

On a typical day, you will:

Develop and sustain a unique, cutting-edge data platform in an innovative and leading data group. This role will include bringing to life rich data pipelines, complex orchestration, real-time data ingestions, data lineage, ML and AI pipeline serving, and incorporation of additional advanced tools and the latest technologies.
Optimize advanced data pipeline infrastructure to ensure reliability, scalability, robustness, and efficiency across AWS, GCP, and Azure environments.
Partner with Data Engineers, Data Analysts, and Data Scientists to understand specific requirements, optimizing data layout and infrastructure for various use cases.

Qualifications:

5+ years in roles such as Data Platform Engineer, Data Engineer, or Software Engineer.
Proven experience in designing and developing comprehensive data platforms.
Strong proficiency in Python, including Object-Oriented Programming, database integration, performance optimization, and parallelization.
Expertise in web scraping using Python libraries such as Scrapy, BeautifulSoup, and Selenium.
Skilled in batch and real-time data processing techniques.
Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and their data services.
Proficient with cloud-based databases (e.g., Google BigQuery, Snowflake), data modeling, data warehousing, and ETL design patterns.
Experience with tools like Docker and Kubernetes for containerization and orchestration.
Familiarity with Infrastructure as Code (IaC) tools such as Terraform.
Comfortable writing, communicating, and presenting in English.
B.Sc in Computer Science, Engineering, or a related field (Master’s degree advantage).