Senior Analytics Engineer

Role Overview

Togetherwork is hiring a Senior Analytics Engineer (hands-on individual contributor) to own the transformation layer of its data platform. You will build trusted, “gold standard” dimensional models that enable self-service analytics across the organization.

Responsibilities

• Gold Standard Data Modeling:
  • Design, build, and maintain dimensional (star schema) models in Redshift as the single source of truth.
  • Power self-service analytics for business users via Sigma and Power BI.
• Data Transformation (dbt):
  • Own end-to-end transformations from raw warehouse data into staging, intermediate, and mart layers.
  • Use modern analytics engineering best practices, including testing.
• AI-Augmented Development:
  • Use AI coding tools to accelerate model development, generate/validate dbt transformations, write tests, and explore data patterns.
• Data Quality & Governance:
  • Define and enforce quality standards, testing frameworks, and documentation so stakeholders can self-serve reliably.
• Cross-Functional Partnership:
  • Translate business requirements from product, finance, and operations into reliable data models.
• Performance & Scalability:
  • Optimize queries, models, and pipelines as data volume and complexity grow.
• AI/ML Enablement:
  • Build clean datasets that support data science and AI/ML initiatives by reducing data prep time.

Requirements

• 5+ years in analytics engineering and/or data engineering with direct ownership of data model design and delivery.
• Strong dimensional modeling expertise (e.g., star schema) and dbt (non-negotiable).
• Hands-on experience with cloud data warehouses: Redshift and/or Snowflake.
• Ability to translate business requirements into models usable by non-technical stakeholders.
• Experience leading data projects end to end in small, fast-moving teams.
• Comfortable working in Agile environments with shifting priorities.

Preferred Qualifications

• Experience in a multi-product SaaS environment.
• Hands-on dashboard/report building in Sigma or Power BI.
• Familiarity with data ingestion tools.
• Exposure to AI/ML workflows and feature engineering.