Analytics Engineer

TO APPLY:

PLEASE SEND YOUR CV TO [email protected] WITH THE SUBJECT LINE ‘BCC Application – Analytics Engineer’

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Analytics Engineers at Depop help the business understand how its performing and what to do next. We work across all data domains to support our internal partners in building high-quality, analysis-ready datasets. As a member of the team, you’ll work with engineers, data scientists, analysts and product managers who are passionate about building high quality products.

You will help bridge the gap between Engineering and the business to build sources of truth for our business definitions and core datasets. You will use tooling such as Airflow, dbt, Looker and Databricks to develop these models. You will also help to set standards and guidelines so that we have improved productivity for our internal users.

Want to find out more about Depop & our engineering team?
We write about technology, people and smart engineering right here – https://engineering.depop.com/

Responsibilities

• Design and build data models for Business Insights and Data Science.
• Work with data consumers to understand their needs and deliver solutions that meet their needs.
• Develop tooling and services to help develop our Looker instance.
• Support BI users and developers in developing self-serve models.
• Identify areas of improvement of our data practices to improve the developer experience.
• Seek feedback on existing data models and work with consumers to improve them
• Promote best practices in developing cost and time efficient models and self-serve analytics.

Requirements

• Proficiency in SQL using cloud data warehouses (e.g. Databricks, BigQuery, Athena) and comfortable building performant queries.
• Experience designing ELT pipelines using dbt or similar.
• Knowledge of data modelling and warehousing best practices.
• Experience with engineering best practices such as testing, standards, reviews and automation.
• Comfortable working in a fast paced environment and able to respond to change.
• Passion for learning new things and keeping on top of the latest developments in data engineering.
• Experience in working with version control (e.g. Git).

Bonus points if you have some of the following:

• Experience using Looker and LookML.
• Experience using Airflow or Databricks.
• Experience using shell scripting or working with APIs.
• Domain knowledge in either commercial reporting, product analytics, adtech or marketing analytics.