Job Title: Senior Data Analyst
Skyline AI was recently acquired by JLL (NYSE: JLL), a leading professional services and investment management firm specializing in real estate. We are now part of a Fortune 500 company, with operations in over 80 countries, a workforce of nearly 100,000 individuals around the world, and annual revenue of almost $20B. Within JLL, we are part of JLL Technologies, a strategic business group whose mission is to leverage technology to increase the value and liquidity of the world’s buildings.
The Skyline AI team has been embedded within JLL Technologies to continue our mission of transforming commercial real estate with data science. We develop a platform that collects data from dozens of sources and uses AI and data science to extract insights for making fast and optimal business decisions. We have assembled an excellent team of leading data engineers, software developers, designers, product managers, and data scientists working towards this goal.
Our recently refurbished offices are in Tel-Aviv and we employ a hybrid, work from home model.
Highlights:
- Best of both worlds - we are a small site and operate similarly to how we did as a startup, but now with the resources of a Fortune 500 company
- Experience with rich, diverse data - one of the truly unique aspects of our domain is the tremendous diversity of data, including dozens of sources and spanning thousands of data points
- Impact - we are a small team working to impact a multi-billion dollar business
- Work alongside amazing talent with the opportunity to broaden your horizons in cloud tech stacks, data wrangling, communication skills, leadership and much more.
Responsibilities:
As a Senior Data Analyst, your typical day-to-day activities will include:
- Developing Data Pipelines: Utilize SQL and Python to create, scale, and optimize advanced data pipelines within Google Cloud (BigQuery) and AWS ecosystems.
- Exploring and Integrating Data Sources: Identify, research, and incorporate new data sources to enhance our data lake.
- Ensuring Data Integrity: Maintain the quality, integrity, and freshness of data, adhering to best practices in data management.
- Collaboration: Work closely with various stakeholders across the organization to support business-driven data initiatives and serve data to platform app and ds teams
Experience: 4+ years in roles such as data analyst, BI developer, data engineer, or data scientist.
SQL Proficiency: Expertise in writing complex SQL queries.
Data Modeling: Strong understanding of data model design.
Integration Expertise: Proven experience in integrating multiple data sources and working with various cloud database technologies.
Library Familiarity: Knowledge of data processing libraries such as Pandas, Polars, or PySpark.
Analytical Skills: Capability to extract valuable insights from large, multi-dimensional, and multi-format datasets.
Communication Skills: Good written, verbal, and presentation skills in English.
Educational Background: Bachelor’s degree in Computer Science, Industrial Engineering, Information Systems, or a related field.
Additional Skills (Preferred but not Required):
Experience with ETL tools and frameworks.
Familiarity with cloud-based databases such as Google BigQuery or Snowflake.
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