Summary

As a Senior Analytics Engineer, you’ll play a pivotal role at the intersection of data engineering, analytics, and business strategy. You'll apply software engineering principles—version control, CI/CD, testing, and documentation—to the analytics workflow, building scalable and trusted data models. You are a builder who thrives on transforming complex, raw data into enterprise-grade datasets that enable informed decisions across the organization.

In this role, you’ll:

1. Design, develop, and maintain robust, scalable data models and transformation pipelines using dbt and SQL—with a special emphasis on expert-level data modeling in dbt—to support analytics and business intelligence across the company.
2. Collaborate with stakeholders in Finance, Sales, Marketing, and Product to translate business requirements into technical specifications for reliable datasets.
3. Apply software engineering best practices, including Git version control, CI/CD, automated testing, and documentation, to ensure data quality and maintainability.
4. Own and enhance the data architecture within our cloud data warehouses (Snowflake/Redshift/Databricks), optimizing for performance, scalability, and cost-effectiveness.
5. Develop and manage data integrations from source systems (e.g., Salesforce, NetSuite, Pendo) using tools like Fivetran and custom Python scripts.
6. Mentor engineers and analysts on advanced dbt data modeling techniques and the effective use of our data stack.
7. Contribute to our data governance framework by establishing and enforcing standards for data quality, consistency, and metric definition.

We’re looking for candidates who have:

1. 5+ years of professional experience in analytics engineering, data engineering, or BI development, with a record of shipping data products to production.
2. Expert-level proficiency in SQL and deep experience with data modeling techniques, especially building and optimizing complex data models in dbt for scalable analytics use cases.
3. Extensive hands-on experience building, testing, and deploying dbt projects in a complex business environment.
4. Strong programming skills in Python for data manipulation and automation.
5. Experience with modern cloud data warehouses (Snowflake, BigQuery, Databricks).
6. Proven ability to work cross-functionally, translating ambiguous business questions into well-defined, quantitative solutions.
7. Experience with version control systems such as Git and CI/CD workflows.

Nice to have experience:

1. Experience using AI-assisted IDEs (e.g., Cursor, Windsurf) or AI code assistants to accelerate dbt model development and improve code quality.
2. Familiarity with data orchestration frameworks like Dagster or Airflow.
3. Experience working in a B2B SaaS environment with an understanding of go-to-market strategies and business metrics (e.g., ARR, LTV:CAC, Customer Health Score).
4. An interest in cryptocurrencies and blockchain technology—we can help you learn!

Technologies we use:

1. dbt
2. Databricks
3. Fivetran
4. Dagster
5. Airflow
6. Python
7. Tableau
8. Git
9. AWS
10. Salesforce
11. Netsuite
12. Pendo

This position is ineligible for visa sponsorship.

Skills

• Analytical Thinking
• Communications Skills
• Development
• Software Engineering
• SQL
• Team Collaboration