Data Developer - Contract

at  esurv

Job Profile:
Trading since 1989, e.surv Chartered Surveyors is the UK’s number one residential surveyor and the largest provider of property risk expertise and residential surveying services. To put it into numbers, we complete more than one property inspection every 12 seconds and employ over 600 surveyors from Land’s End to John O’Groats and Northern Ireland. This gives us the flexibility to offer nationwide coverage combined with invaluable local knowledge.
We’re part of the LSL Property Services Group PLC, which includes household names Your Move and Reeds Rains as well as the mortgage network PRIMIS. We work with lenders, intermediaries, social housing entities and estate agents in addition to private customers.

MAIN ACCOUNTABILITIES:

• Build a centralised data store for the data science team.
• Set up Airflow or an alternative tool.
• Push existing development ETL pipelines to production.
• Ingesting and processing new datasets from various sources (including web scraping) and varying formats (including JSON and HTML) in the ETL.
• Extracting meaningful information from lengthy text fields (advanced string manipulation is enough).
• Help improve in-house address matching algorithm.
• Reporting on ETL outputs.
• Additional support for the data science team.

APPLY

If you feel you match our requirements and are looking for your next career challenge, or for a confidential discussion on the full details of this role please contact Mike Brett on 07767 100622 or recruitment@esurv.co.uk – alternatively apply with your CV and covering letter for a quick response. Our team are also available out of hours on 07794 392858.
LSL Property Services are dedicated to protecting your data – our Recruitment Privacy Notice can be viewed HERE

• Experience developing and maintaining complex data pipelines. Familiar with relevant tools (e.g. Airflow, SSIS).
• Strong Python programming skills.
• Excellent SQL skills; experience with PostgreSQL.
• Familiarity with data warehousing and cloud platforms (e.g. Azure).
• Knowledge of big data technologies.
• Knowledge of optimising data processes and infrastructure for efficiency, scalability, and cost-effectiveness.
• Experience with property data is a bonus.
• Geospatial experience is a bonus.