26WD95901

Position Overview
 

We are looking for an experienced Data Architect to join our Customer Success Analytics team within Customer Success. This role will serve as the technical cornerstone of our team, responsible for designing and building the foundational data infrastructure that powers our analytics. You will lead the effort to architect a unified, scalable, and governed data ecosystem, transforming disparate data sources into a single source of truth that enables critical insights for retention and growth.
 

Responsibilities
 

As a Data Architect, you are responsible for defining the technical vision and structure of our data platform. You will move beyond ad-hoc querying to build robust, automated, and modular data pipelines in partnership with data engineers and analysts across the company.

• Architect and implement a comprehensive data strategy on Snowflake, moving the team from manual processes to a fully automated, resilient data warehouse environment

• Design and maintain scalable dimensional data models that consolidate logic from various internal and external sources, ensuring consistency across all reporting and analytics

• Develop and manage end-to-end data transformation pipelines using dbt (data build tool) and Python, ensuring rigorous testing, documentation, and version control

• Orchestrate complex workflows using tools like Airflow to ensure timely and reliable data delivery for downstream dashboards and stakeholders

• Establish data governance frameworks, including data quality monitoring, lineage tracking, and naming standards, to ensure trust and accuracy in our metrics

• Audit and streamline existing legacy code and processes, refactoring them into modern, efficient, and maintainable architectures

• Act as the technical subject matter expert, mentoring the team on SQL best practices, data modeling techniques, and engineering standards

• Collaborate with business stakeholders and analysts to translate complex business requirements into clean, performant technical solutions

Minimum Qualifications
 

• 8+ Years of relevant work experience in Data Architecture, Data Engineering, or BI Architecture

• Expert-level proficiency with Snowflake architecture, including performance tuning, cost optimization, and advanced SQL (CTEs, window functions)

• Deep hands-on experience with the modern data stack, specifically dbt for transformation and modeling

• Strong proficiency in Python for data manipulation, scripting, and automation

• Experience with workflow orchestration tools (e.g., Airflow) to manage pipeline dependencies

• Strong understanding of Git-based workflows, CI/CD, and code review processes

• Experience designing data structures that integrate seamlessly with BI tools (e.g., Power BI, Tableau)

• Experience with the post-purchase journey of a cloud product company is a strong plus

• Knowledge of SaaS business models and key metrics (e.g., Retention, Churn, Adoption) is preferred

The Ideal Candidate

The ideal candidate will have a visionary mindset with the technical expertise to execute it and will be a self‑starter who takes ownership and drives initiatives forward with minimal oversight. You are a "builder" who thrives on creating structure from ambiguity, someone who can look at a scattered data landscape and architect a cohesive, efficient system. A deep understanding of modern cloud data warehousing, a passion for clean code and architecture, and the ability to bridge the gap between technical complexity and business value is essential.
 

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