Data Warehouse Developer

ClearGov•Toronto, ON

2d•Hybrid

About The Position

ClearGov is seeking a Data Warehouse Developer with a passion for learning, a kind heart, a positive attitude, and a great sense of humor to join their growing data team. This role is responsible for transforming raw signals from sales, success, and product tools into a unified "source of truth." The ideal candidate understands the importance of data reliability and is comfortable with complex SQL, Python pipelines, and data governance frameworks. The Data Warehouse Developer will be a key player in executing ClearGov's mission to help local governments and school districts improve their transparency and accountability.

Requirements

5+ years of Experience with modern data stack tools (e.g., Databricks, dbt, Airflow, Fivetran/Airbyte).
Knowledge of Gong conversation intelligence data and how to link it to CRM outcomes.
Understanding of SaaS metrics (CAC, LTV, Net Retention, Churn).
Strong knowledge of Go-To-Market operations.
Comfortable writing complex SQL window functions.
Comfortable orchestrating Python pipelines.
Comfortable discussing data governance frameworks.

Nice To Haves

Self-motivated, self-starter with a zeal to win
Great communicator; strong oral and written skills
Ability to think creatively and innovatively
Hands-on problem solver who enjoys cracking difficult nuts
Quick study – able to pick up and apply new concepts in a hurry
Track record of achievement
Enjoys working on and helping to build outstanding teams
Demonstrates an entrepreneurial spirit and gets stuff done
A sense of humor and don’t take themselves too seriously

Responsibilities

Design and maintain robust data pipelines using the Medallion Architecture (Bronze/Silver/Gold) to ensure data lineage and scalability.
Ingest and model data from core tech stack tools including Salesforce, Zendesk, Pendo, ChurnZero, and Gong.
Transform disparate data sources into a high-performance Fact/Dimension (Star Schema) architecture.
Implement automated data quality rules and validation checks to ensure accuracy.
Define and enforce data governance standards across the warehouse.
Build and manage alerting and monitoring systems to proactively identify pipeline failures or data drift.
Occasionally build stakeholder-facing dashboards and self-serve layers to visualize GTM KPIs.
Investigate and fix the root cause of data bugs in source systems.
Bridge the gap between technical infrastructure and business requirements from Sales and Marketing leaders.
Take pride in clean code and clean data.