Senior Analytics Engineer (EU Timezones Only)

Requisitos e responsabilidades

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The Data Team

Data Project Management: Based on business needs, we sort requests, refine requirements and ACs with business and/or data stakeholders, prioritise, plan and executive while communicating proactive and frequently to ensure visibility and a well connected feedback loop with involved parties (reviewer, data stakeholder, business stakeholder)
Applied Analytics & Data Science: Data Exploration, Defining appropriate and agile analytics approach. We aim for simplicity and interpretability but don't shy away from complexity when faced with it. All new projects have a strong Data Science component during the first MVP iteration
Analytics Engineering: Data Modelling and Transformations to serve build, maintain and scale our Analytics Pipelines. Practically, as soon as an MVP gets validated by different stakeholders, we start implementing it and improving it iteratively in our dbt project. Testing and data observability is a highly important component. Proper architecture that helps manage TechDebt is another key element here as well.

Expectations | Duties

You will work on Data Modelling and Analytics Engineering project to improve, enrich and maintain our data models and Analytics pipelines. Those projects will be in close collaboration with the head of Data & Analytics as the main stakeholder. The objective of those project is to further enable data analytics and scientist from the team to bring more impact to the business use cases they are working on in collaboration with business teams.
You will be responsible for contributing effectively to our code base: building, testing, reviewing and maintaining solid analytics pipelines using SQL and dbt. Help managing TechDebt and improving engineering practices and the project's architecture are also important responsibilities for this role. Solid methodical testing is key here to strengthen Data Observability.
You are expected to gradually own some aspects of the team's responsibilities (some parts of the code base, , have a strong saying in how the analytics project's architecture should evolve, contribute to team's evolution and continuous growth, help data analysts and scientist improve and strengthen their engineering skills ...)
You will be expected to speak up your mind and contribute proactively and effectively to improving the team's practices, cohesion, impact and mission
You are expected to be highly autonomous and show a sense of ownership and ability to effectively manage your own projects and stakeholders. This should be fulfilled with minimum guidance from the Head of Data & Analytics
You will help mentoring more junior members and sharing knowledge and practices within the team to level up everyone's skills

Requirements

University Degree in Engineering, Computer Science or Applied Mathematics
A minimum of 4 years of experience in Data or Analytics Engineering
Excellent hands on skills in Data Modelling
Excellent SQL skills (even better if this is coupled with dbt experience or a similar sql based data modelling tool)
Excellent Engineering skills (testing, clean coding, peer-reviewing, CD/CI, git workflows, agile workflows, etc…)
Previous experience working with modern data stack tools and cloud based data warehouse (BQ, Snowflake, Redshift,..)
Sound business acumen to mange your own projects and your business stakeholders
Self-Starter with the ability to work autonomously and own ones projects fully
Excellent written and verbal communication skills (English)
Comfortable in a remote work environment (we are a remote-first organisation)

Good to Have:

Prior experience with some of the tools we use in our Data-Stack (Amplitude, dbt, BigQuery, Metabase)
Good analytical and statistical intuition
Hands-on Data Analysis skills
Prior experience managing modern dbt data pipelines
Prior experience in an agile start-up environment