Data Engineer

looking for a Data Engineer to help build and scale our analytics data infrastructure. In this role, you will work closely with analysts and business stakeholders to design reliable data models and support the development of a centralized semantic layer used across the company.You will play a key role in improving the structure, reliability, and usability of our data stack. This includes building and maintaining dbt models, supporting data pipelines, and ensuring analysts have access to clean, well-documented, and consistent data.This role is ideal for someone who enjoys working at the intersection of data engineering and analytics - translating business needs into scalable data models and enabling teams to move faster with trusted data.ResponsibilitiesDesign and implement data models that support analytics across key business domains such as GTM, CX, and FinanceBuild and maintain transformation workflows using dbtWork closely with analysts to translate business questions into scalable and reusable data modelsHelp define and implement a structured semantic layer that enables consistent metrics across the companyImprove the reliability and clarity of the analytics data stack by centralizing logic into well-designed data modelsSupport the ingestion and transformation of data from various sources using tools such as Fivetran and AirbyteContribute to improving data quality, monitoring, and documentation practicesHelp establish best practices for analytics modeling and data usage across teamsActively leverage AI tools (e.g.

Cursor, LLM-based assistants) to improve development speed, data modeling, and data workflowsRequirements: 2-4 years of experience in bi/data engineering, analytics engineering or a similar role.Strong SQL skills and experience working with modern data warehouses.Experience building and maintaining data models for analytics.Familiarity with modern data stack tools such as dbt, Snowflake/Bigquery, Fivetran/Rivery, or similar.Experience collaborating with analysts or BI teams.Familiarity with Python for data-related tasks (scripting, automation, or tooling).Hands-on experience using AI tools (e.g. Cursor, LLMs) as part of day-to-day development workflows.Strong problem-solving skills and the ability to work in evolving data environments.Clear communicator who can work effectively with both technical and non-technical stakeholders.This position is open to all candidates.