Job Summary
This is an exciting time to join the growing Data Team at Remote, which today consists of over 15 Data Engineers, Analytics Engineers and Data Analysts spread across 10+ countries. Throughout the team we're focused on driving business value through impactful decision making. We're in a transformative period where we're laying the foundations for scalable company growth across our data platform, which truly serves every part of the Remote business. This team would be a great fit for anyone who loves working collaboratively on challenging data problems, and making an impact with their work. We're using a variety of modern data tooling on the AWS platform, such as Snowflake and dbt, with SQL and python being extensively employed.
- Minimum Qualification : Degree
- Experience Level : Senior level
- Experience Length : 5 years
Job Description/Requirements
What you bring:
- Experience in analytics engineering; high-growth tech company experience is a plus
- Strong experience using data transformation frameworks (e.g. dbt) and data warehouses (e.g. Redshift), strong proficiency in SQL
- Strong knowledge in data modelling techniques (Kimball, Data Vault, etc)
- Solid Experience with data visualization tools (e.g. Metabase)
- Strong affinity towards well crafted software - testing, knowledge of best practices, experience with CI/CD (e.g. Gitlab, Github, Jenkins)
- A self-starter mentality and the ability to thrive in an unstructured and fast-paced environment
- Proven collaboration and communication skills
- Experience in dealing with ambiguity, working together with stakeholders on taking abstract concepts and turning them into data models that can answer a variety of questions
- Writes and speaks fluent English
- It's not required to have experience working remotely, but considered a plus
Key Responsibilities:
- DBT Modelling:
- Design, develop, and maintain dbt (Data Build Tool) models for data transformation and analysis, providing clean and reliable data to end users enabling them to get accurate and consistent answers by self-serving on BI tools.
- Collaborate with Data Analysts and Business Stakeholders to understand their reporting and analysis needs and translate them into DBT models.
- Own our internal dbt conventions and best practices, keeping our code-base clean and efficient (including code reviews for peers).
- Data Analytics & Monitoring:
- Ensure data quality and consistency by implementing data testing, validation and cleansing techniques.
- Implement monitoring solutions to track the health and performance of the data present in our warehouse.
- Train business users on how to use data visualisation tools.
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