Analytics Engineer
MachinifyFull Time
Mid-level (3 to 4 years)
Candidates should have over 4 years of experience in Data Warehouse Engineering, Data Engineering, Analytics Engineering, or a similar role. They must possess a deep understanding of data modeling concepts, including when traditional approaches are effective and when they are not, and have experience designing scalable data models and ETL pipelines with a focus on ease of use, high performance, and scalability. Proficiency in modern data platforms and best practices for scalability and performance is expected, along with AI fluency for tasks like scaffolding SQL, brainstorming data models, and drafting documentation, with careful validation of outputs. The ability to self-organize and manage projects end-to-end, from requirements gathering to delivery, is essential.
The Data Warehouse Engineer will build trusted data products by designing scalable and high-quality pipelines using Airflow, dbt, and Databricks, modeling business-critical metrics like ARR, churn, and NRR to enable stakeholder self-service. They will shape the technical direction by guiding architectural decisions, tooling choices, and strategies to optimize data storage and the analytics landscape. Additionally, they will enable self-service analytics by partnering with stakeholders to understand their analytical needs and creating data products that connect raw data to actionable insights, prioritizing impact in their work.
Automation platform for web application workflows
Zapier connects various web applications to help users automate their workflows and improve productivity. It allows users to create 'Zaps,' which are automated workflows that link different apps to carry out specific tasks without needing technical skills. This platform is particularly beneficial for small to medium-sized businesses and individual professionals who want to save time on repetitive tasks. Unlike many competitors, Zapier offers a user-friendly interface that makes it easy for anyone to set up automations. The company operates on a subscription model, providing different pricing tiers based on the number of Zaps and tasks a user requires, with the goal of making automation accessible to a wider audience.