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Business Intelligence And Data Engineer Position In Spain
hace 1 mes
At Spotahome, we are revolutionising the way people rent housing. We are an online marketplace that offers everyone in the world the most comprehensive listing of apartments, rooms, and student housing in their city of destination.
We personally check thousands of places taking professional photography, making cool HD video tours, designing floor plans, and getting tons of details of each accommodation so potential tenants can securely book a whole apartment or rent an individual room in a flat or a student residence all from the comfort of their couch.
We are a fast-growing startup backed by top VC companies in the world (Kleiner Perkins, Seaya Ventures, Passion Capital...) in our journey to forever change the way people find housing.
Our business is certainly complex:
We are a double-sided marketplace where we need to serve two different types of customers: Tenants finding a home to live in, and Landlords wanting to securely rent out their properties and make a profit from it.
Understanding our marketplace dynamics and customer behaviour is definitely a key challenge for Spotahome success, and our data, analytics, and business intelligence function plays a crucial role in this, and thus in Spotahome's success.
We are looking for a talented Data Engineer and Business Intelligence Specialist to join our team. As a Data Engineer and Business Intelligence Specialist, you will work closely with the different departments of the company to build beautiful insights with the company data.
The data and analytics team owns a big chunk of Spotahome's stack:
A data pipeline that moves data from our transactional databases and our front-end analytical systems (Segment, Amplitude, Google Analytics) to a data lake in BigQuery.
A set of ETLs in DBT that transform that data and load it into our Postgres Data Warehouse.
Self-service dashboarding tools to access this data: Metabase.
A dbt (data build tool)-based pipeline to transform Data Lake data into a feature store for statistical and machine learning models.
A set of statistical and Machine Learning models trained and executed against this feature store (mostly written in Python).
A Python-based REST API so other systems can consume the output of these models.
Within this stack, as a Data Engineer and Business Intelligence Specialist, you will be heavily immersed into our data pipelines, data lake and data warehouse evolution and maintenance, along with the self-service dashboarding tools in Metabase, collaborating as well with our data engineers and data scientists in working in our feature store and dbt pipeline.
Within this context, your responsibilities will be:
First and foremost, you will be an advocate for data-informed decision making in Spotahome.
You will participate in educating key roles in the company on how to get better insights from our data and participate with them in decision making.
You will partner up with the Business Analysts, product managers, and data scientists in order to achieve this.
You will be the owner of the data the company will base their decision making on.
That implies:
Fetching data from heterogeneous sources, consolidating it in a reliable and automated reporting system, and ensuring it is accessible and understandable for the key decision makers.
You will design and implement the processes and the reports to analyse all company KPIs, and work closely with the product, operations, marketing, and business teams to analyse those KPIs.
You shall own different dashboards and reports used in weekly, monthly, and quarterly reporting, and that will imply working closely with Metabase as the main dashboarding tool.
You will maintain and evolve the tech stack supporting all the processes above.
That shall imply:
Database modelling and performance:
You will work with our data lake (BigQuery) and our data warehouse (Postgres).
SQL querying for report, ETL (DBT), and dashboard creations.
Getting exposed to the entire Spotahome transactional architecture (PHP microservices persisted in MongoDB and MySQL) to understand the data model and be able to design proper data pipeline solutions.
We are a fast-paced StartUp environment, therefore you will need to dive comfortably into high ambiguity situations.
It is a big challenge that requires an analytical mindset.
In the future, should the data and analytics team grow, there could be an opportunity to jump into a team leadership role.
