Senior Analytics Engineer

About the Role

Are you passionate about turning raw data into actionable insights and enabling data-driven decision-makingAs an Analytics Engineer, you will play a critical role in shaping our data ecosystem and ensuring that our teams have access to accurate, well-structured, and timely insights.

You ll collaborate closely with different business functions to design and implement scalable data models, track key performance metrics, and optimize data workflows. Your work will directly impact how we measure product success, marketing effectiveness, and customer engagement.

What Youll Do

Collaboration & Enablement

• Partner with cross-functional teams to democratize data access and improve self-serve analytics capabilities.


• Partner with cross-functional teams to gather requirements and implement reporting/dashboards which allow those teams to improve performance


• Create and maintain clear documentation for data models, metrics, and best practices.

Data Engineering & Pipeline Optimization

• Use dbt (Data Build Tool) to build, test, and optimize scalable data models.


• Implement semantic models within our Business Intelligence platform


• Implement reports/dashboards in our Business Intelligence platform which leverage our semantic model


• Work with cloud data warehouses (BigQuery, Snowflake, or Redshift) to ensure efficient data transformation and storage.


• Implement automated data quality checks to maintain integrity and reliability across datasets.

What You ll Need

Technical Skills & Experience

• 5+ years of experience in analytics engineering


• Strong SQL skills and experience working with data warehouses (BigQuery, Snowflake, or Redshift).


• Strong reporting/dashboarding skills leveraging a modern Business Intelligence platform with a Semantic Layer (Omni, Looker, Lightdash, etc)


• Hands-on experience with dbt for data modelling and transformation.

Soft Skills & Collaboration

• Ability to work cross-functionally with different stakeholders.


• Excellent problem-solving skills and a structured approach to data challenges.


• Strong written and verbal communication skills to translate complex data concepts for non-technical stakeholders.


• Self-motivated and eager to optimize and automate data processes wherever possible.