Tech Stack

Description

Build and scale the enterprise analytics foundation by owning core data models, from raw ingestion to presentation-ready datasets, and partnering closely with business teams to ensure trusted, well-modeled data is available across the organization.

Requirements

• Bachelor's degree in a technical or math-based discipline, or equivalent practical experience.
• Minimum of 8 years of experience in data analytics or engineering.
• Expert-level SQL knowledge, with proficiency in large-scale data manipulation and performance optimization.
• Experience leading cross-functional projects from ideation through execution.
• Developed experience with data architecture, pipelines, and ELT processes.
• Experience with dbt, Snowflake and Fivetran
• Excellent attention to detail.
• Customer-centric mindset.
• Excellent communication skills.
• Critical thinking and problem-solving using data.
• Proficiency in Python and/or R.

Responsibilities

• Design, build, and maintain scalable, well-documented data models that power executive dashboards, financial reporting, and operational analytics.
• Own the entire ELT process from raw source data to analytics-ready data models.
• Partner with upstream data ingestion teams to improve source data quality, reliability, and observability.
• Define and enforce data quality standards through automated testing, documentation, and monitoring.
• Contribute to data governance efforts including access controls, data lineage, documentation, and metric consistency.
• Collaborate closely with Finance, Revenue Operations, GTM, Product, and Analytics teams to translate business requirements into scalable data models.
• Enable data literacy and self-service analytics through a Data Champions program.
• Establish and contribute to analytics engineering best practices and shared documentation.
• Review code and mentor junior analytics engineers.
• Identify opportunities to improve performance, cost efficiency, and developer experience.