Senior Analytics Engineer

How you'll help us achieve it

Wave is now the largest financial institution in Senegal, with over 7 million users. And, we’re still in the early days of our product roadmap and potential impact on people’s everyday lives. As a senior analytics engineer, you will work to make Wave’s data easy, safe, and reliable to use, enabling better products for our customers. 

Key focus areas for this role will be;

• Leading dimensional design to structure Wave’s analytics data in ways that are helpful for human and AI end users. Examples of what you might work on:
• Building out facts, dimensions and One Big Tables (OBTs) as appropriate for a focus area at Wave. 
• Understanding the tradeoffs between creating semantic layers at different parts of the stack with a final recommendation. 
• Standardizing metric creation and usage. 
• Building out ways to make it easy to add context for LLMs to data models. 
• Managing our extensive snowflake estate with a strong analytical mindset. Examples of what you mind work on: 
• Finding patterns that are repeated frequently and optimizing them. 
• Building tools to identify and turn off stale/unused models. 
• Evaluating the impact of an optimization on costs and performance. 
• Building tools to improve the analytics development experience. Examples of what you mind work on:
• Creating helpful dbt macros. 
• CI/CD checks that catch possibly exploding joins. 
• Reducing the pain of iterating on metric design. 

Outside of the focus areas, folk in this role will also;

• Be responsible for the design, build and health of all of our ETL pipelines. Part of the role includes being ‘on-duty’. On duty responsibilities require that you have a working understanding of most parts of the stack. 
• Champion best practice across data. 
• Be a key partner in the road map of the data platform team.

Key details

• This is a fully remote role. Candidates must be based in one of our talent hub countries (UK, Spain, USA (east coast), Canada, Kenya and Ghana) or in one of our operating markets in Africa including Senegal, Côte d'Ivoire, or Burkina Faso.
• Wave provides a yearly $1,200 stipend to support co-working meet ups with teammates.
• Remote team members are expected to travel to our operational markets (e.g. Senegal or Côte d'Ivoire) at least once a year. Exceptions apply, but we’ve found this key to understanding our users and product.
• Our salaries are competitive and are calculated using a transparent formula. For this role, depending on your level and location, we offer a salary of $133,100 - $178,200 USD, paid in your local currency equivalent plus a generous equity package.
• Major benefits:
  • Subsidized health insurance for you and your dependents and retirement contributions (both vary from country to country).
  • 6 months of fully paid parental leave and subsidized fertility assistance.
  • Flexible vacation, with most folks taking between 30-40 days per year. 
  • $10,000 annual charitable donation matching.

Requirements

• 5+ years as an analytics or data engineer. Software engineering experience that focused on data platforms also counts. 
• 3+ years of involved experience with Snowflake.This should ideally include experience with performance optimization.
• Experience with dimensional modeling. Ideally you would have built two or more dimensional marts.
• Strong python, sql and dbt experience.
• Familiarity with managing an orchestration platform like dagster or airflow. 

You might be a good fit if you 

• Are proficient in SQL and Python.
• Are a self-starter that excels at exploring problems and collaborating closely with operations teams to drive growth through data. 
• Have excellent focus, prioritizing your research and work using an iterative approach (you know when a project is good enough to stop, and you rarely get lost in details).
• Are able to compellingly present your findings to technical and non-technical audiences and make proactive recommendations based on data. 
• You excel at choosing the right complexity of analysis for any given business problem, from simple SQL queries to complex experimentation.