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Data Engineer

Published8th June
SectorInvestment, Asset Management & VCs
Job Type
Job TypePermanent
ConsultantDuncan Kennedy

PropTech Data Engineer role based Remotely in the US

About our client

Are you interested in building state of the art analytics products to create advanced products from the ground up? Our client is in the process of migrating to the cloud to boost their ability to effectively empower their data analyses and build custom modeling software. The company is looking for a Data Engineer (DE) to join the Innovation, Data & Analytics team. This team member will work cross functionally with app developers, data analysts, consultants, and data scientists to build scalable architecture for both reporting and advanced analytics. The DE will work as a database administrator and cloud developer to generate schemas and automate the ETL process. The DE will create analytical data structures, such as OLAP cubes, for quick and easy data access from Excel, Power BI, Python, R, etc. The DE will work with data scientists to enhance data flow to models and aid in the feature engineering process.

Our client is a national leader in providing strategic economic guidance to the real estate industry. Founded in 1967, the company is a pioneer in bridging market and financial feasibility, consumer research, and industry intelligence. Their professionals are widely respected for their ability to assess economic and market directions, and to translate these trends into project concepts and financial guidance.

Key duties include:
  • Participate in the building of current data products and solutions
  • Develop the ability to use our client’s current visualization tools as well as define and create new ones
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Work with stakeholders to assist with data-related technical issues and support their data needs
Minimum Technical qualifications:
  • Experience running production cloud systems
  • Security, monitoring, diagnostics, deployment strategy
  • Strong DevOps methodology
  • Understanding of GIS and spatial data analysis
  • Storage data types and spatially indexed data structures
  • At least 2 years of experience working on data pipelines
  • Technical knowledge with at least 2 years of experience in most of the following:
  • Database architecture and design in SQL
  • Data warehouse architecture and design, specifically OLAP
  • ETL processes utilizing DAG in a framework (Airflow, Luigi, etc.)
  • Linux command line (simple commands)
  • Cloud architecture, data storage and pipelines
  • AWS, GCP, or Azure
  • Cloud tools: File storage, ETL, serverless, database
  • Programming technology
  • Must have: Python, SQL
  • Nice to have: R
  • Experience in Developing and supporting large scale geospatial pipelines
Other Qualifications:
  • Basic understanding of the real estate industry or economics
  • Bachelor’s degree in engineering, economics, finance, or other quantitative field
  • Ability to work independently and hit deadlines
  • Ability to communicate complex technical topics in an easily digestible manner

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