Senior Analytics Engineer

We are seeking a highly skilled and experienced Senior Analytics Engineer to join our team. This pivotal role sits at the intersection of data analysis and data engineering, leveraging software engineering best practices to deliver reliable, scalable, and easy-to-use data models and analytics solutions.

The ideal candidate will have a deep mastery of SQL and dbt for robust data transformation, coupled with significant hands-on experience across the Modern Data Stack. They should be comfortable touching any part of the stack that empowers analysis, from orchestrating dbt runs in Airflow and writing simple Python data processes, to building final visualizations in Sigma and partnering directly with the business. This role is instrumental in bridging the gap between raw data and business insights, ensuring high-quality data products and enabling advanced analysis across the company.

Responsibilities

Data Modeling & Transformation: Design, build, and maintain production-grade, tested, and well-documented data models using dbt in Snowflake.

SQL Mastery & Optimization: Write, optimize, and refactor complex SQL to ensure data quality, integrity, and performance across all models.

Pipeline & Orchestration: Build and maintain basic Airflow DAGs to schedule and orchestrate dbt runs and simple data workflows.

Light Engineering: Develop simple data ingestion or processing scripts using Python (eg. using DuckDB, dlt or Polars) for specialized data preparation.

BI & Stakeholder Enablement: Design and maintain high-impact dashboards and reports in Sigma to track KPIs. Translate complex business needs into technical specifications and data models.

Mentorship & Quality: Apply software engineering best practices ( Git, CI/CD) to analytics code and mentor more junior Data Analysts.

Qualifications

Experience: Minimum of 5 years in a data-focused role, with proven experience as an Analytics Engineer or similar data modeling/transformation role.

Core Technical Stack: Mastery of SQL and dbt for production data modeling. Deep experience with Snowflake or a similar cloud data warehouse.

Analytics Tooling: Expertise in Sigma or any modern dataviz tool for visualization and reporting, and hands-on experience with Airflow for orchestration. Some experience with Salesforce data is nice to have.

Programming: Proficiency in Python for scripting and light data manipulation.

Engineering Practice: Strong understanding of version control with Git and applying engineering rigor to analytics work.

Soft Skills: Excellent communication and collaboration skills, with the ability to clearly explain complex topics to non-technical stakeholders.

Hiring process

An intro call with our Senior Talent Acquisition Manager

A technical interview with our engineering manager of Data & Analytics

A code challenge to showcase your python and dbt skills. This is used as the basis of discussion for the next step

A 60/90min code review session, SQL and architecture discussion with the rest of the team

A set of 1:1 30-minute calls with VP of Engineering, engineers, and a product manager

Our Technology Stack

We process billions of events every day. Our data team relies heavily on Snowflake, dbt, and Fivetran for a modern ELT architecture. Our pipelines are orchestrated via Airflow, and our code and CI are managed in Gitlab. Sigma is ourchosen BI platform for empowering the business and our customers with data.

Our Vision as a Team

We are building an engineering team committed to delivering high-quality products and code. We believe in automation to ensure consistent quality, rapid development, and we take pride in our work. We prioritize minimizing unnecessary meetings and value a remote-first, collaborative culture. We rely on automated testing and continuous integration/delivery to build flexible applications.

Applicants who contact employees directly regarding their application will not receive a response. Please submit your application through the designated application form.