Senior Director, Data Engineering & Analytics (Snowflake, Python)

TL;DR

Senior Director, Data Engineering & Analytics (Snowflake, Python): Defines long-term architecture and drives development of a mission-critical, always-on Data Platform, processing millions of utility bills monthly. Focus on architecting, scaling, and leading a data and analytics engineering team at a high-growth SaaS company, with deep expertise in large-scale data operations and promoting evidence-based decision-making.

Location: Remote, must be based in the US, with a preference for candidates in the Eastern Time Zone. Visa sponsorship is not available for this position.

Salary: $183,000–$329,000 annually, plus competitive benefits and equity.

Company

hirify.global is a global utility data and energy solutions platform providing enterprise energy management solutions built on a decade-developed data platform.

What you will do

• Define organizational structure and build, lead, and scale a data and analytics engineering organization.
• Drive technical architecture, decisioning, and execution of data and analytics engineering work as a deep technical expert.
• Align engineering data investments with business goals and long-term strategy, supporting data-centric product development.
• Establish department-wide standards for data platform governance and development, ensuring customer insight.
• Own cross-organizational data platform development and establish a multi-year strategy for data infrastructure and modeling.
• Lead optimization and evolution of Snowflake-based data architecture for exponential data growth.

Requirements

• Expert Data & Analytics leader with demonstrated experience processing and analyzing large-scale datasets (billions of records).
• Deep expertise with Snowflake as a data platform, including performance optimization and cost management.
• Hands-on experience with dbt for transformation, Hex for analytics, and Fivetran/Airbyte for data ingestion.
• Experience building and leading Data & Analytics teams at high-growth SaaS companies.
• 12+ years in the workforce with significant experience in data-intensive environments.
• Proficiency in SQL and Python with demonstrated ability to write optimized queries for large-scale data processing.

Nice to have

• Experience with real-time or near-real-time data processing systems.
• Knowledge of cloud platforms (AWS, Azure, or GCP) and their data services.
• Experience with orchestration tools (Airflow, Dagster).
• Background in energy, utilities, or sustainability sectors.

Culture & Benefits

• Remote-first culture, allowing work from anywhere in the US.
• Flexible PTO, 12 annual company-wide holidays, 10 days of sick leave, bereavement, volunteer, and professional development days off.
• 12 weeks of paid parental leave for all parents.
• Weekly "flex time" with no internal meetings on Friday afternoons.
• 75-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents.
• Supportive engineering culture valuing diversity, empathy, teamwork, trust, and efficiency.