Senior Data Analyst
Toronto, Ontario
Data & Analytics – Analytic Operations /
Full-time /
Remote
About the Role
The Senior Data Analyst is responsible for advancing the maturity of Data Analytics at Wave, combining strong business acumen with analytical expertise. They bridge the gap between technical and non-technical audiences, delivering insights and leveraging data to inform strategy and decision-making for Wave.
Here’s How You Make an Impact:
- Ownership of analytics needs for specific product line(s) for Wave.
- Working with stakeholders to understand their challenges and goals, identifying data analysis opportunities, and developing solutions to drive decision-making.
- Partnering with fellow data analysts and data scientists to develop new analysis tools.
- Delivering documentation that guides other team members toward understanding of critical domain knowledge.
- Improving the Data Analytics team’s practices by identifying areas of friction and implementing solutions.
- Facilitating the creation of reporting dashboards (via Looker), establishing and interpreting the performance of key metrics, and advocating for experimental best practices as we evolve the analytical maturity of the company.
- Extracting and transforming data for use by stakeholders, ensuring data integrity where necessary in partnership with Data Operations.
- Enriching data and applying advanced analytics to projects where appropriate in partnership with Machine Learning.
You Thrive Here By Possessing the Following:
- 5+ years of experience in Analytics, including the application of statistical analysis, experimental design, and modeling/forecasting.
- Advanced SQL skills with experience querying large and complex datasets.Experience using dbt to transform data.
- Experience working with dimensional models (i.e. star schemas).
- Experience with Python for data analysis.
- Expertise in developing reports and dashboards with Looker (or equivalent data visualization platforms).
- Experience with analytics applied to business problems: creating lifecycle metrics, retention/churn analysis, correlation/regression, time series forecasting, etc.
- Ability to effectively communicate complex matters and requirements between audiences, both visually and verbally.
- Proactive, autonomous, and able to partner with business and engineering stakeholders to support the ideation and execution of key projects.
- Possesses business acumen to identify and evaluate key performance indicators and provide recommendations that drive decision-making and propel business value.
Nice to Have:
- Experience with event stream processing via Apache Flink (or similar frameworks).
- Experience with third-party data tools Segment, Amplitude.
- Experience with multiple-product environments or diverse business models.
- Fintech experience, especially with Accounting, Banking or Payroll industries.
