Data Analyst
Role details
Job location
Tech stack
Job description
We're a friendly, dynamic and supportive team. We encourage passion, ambition and collaboration, both in our performance as a team and individually. New ideas are encouraged. We actively promote involvement in the development and direction of our products and services, as well as finding more efficient ways to work. We also love a good work social and team building events. As well as this we offer:
- 25 days' holiday, with optional 5 days unpaid leave per year
- Free parking
- Annual lifestyle allowance of £300 to put towards an activity of your choice
- Cycle to Work scheme and Gym Flex scheme
- Internal coaching/mentoring system throughout your time here
- Focus on training and career progression
- Family friendly policies
- Happy to talk about flexible working
The Opportunity:
The Data Analyst is the subject matter expert for a set of datasets that underpin Landmark's many products and services. You will be responsible for ensuring the quality and currency of the datasets as well as providing support to the wider business on the subject matter.
As the dataset owner you will have the scope to identify and implement any efficiencies whilst performing maintenance activities on the datasets, collaborating with colleagues to share ideas and experiences. You will also be required to support wider team and company improvements and initiatives such as Cloud migration.
In addition, the team also gets involved in project work where you may be asked to contribute based on your technical or domain expertise.
Requirements
The Data Analyst will be inquisitive with a desire to understand and resolve problems. You will also be an effective communicator, with the ability to plan, allocate and manage work for yourself and junior team members. You will also have/be:
- A qualification in GIS or Data related discipline or equivalent professional experience
- Practical experience of working in a data analysis or data curation role
- Practical experience of authoring ETL/ELT processes following current best data governance practises, of problem-solving, and finding efficiencies in already existing data pipelines using technologies such as FME Form/Flow
- Knowledge and experience of languages such as SQL and Python
- Practical experience of database technologies such as Oracle, SQL Server or PostgreSQL/GIS
- Experience in public or private cloud based data tooling & storage experience