Bachelor's degree in Data Analytics, Computer Science, Finance, Accounting, AI & Machine Learning, or related field.
3+ years of experience in analytics engineering, data analysis, or technically focused FP&A.
Strong SQL and Python skills for scalable data and analytics solutions.
Experience designing data models in modern cloud data platforms, preferably Snowflake.
Understanding of financial concepts to align data solutions with business needs.
Demonstrated interest in applying AI/ML to enhance analytics and decision-making.
Data, analytics, or cloud certifications (e.g., Snowflake, Microsoft, dbt) are a plus.
Responsibilities
Shape and advance the FP&A operating model with scalable, automated workflows.
Design and evolve the finance data layer for analysis-ready structures.
Build robust data pipelines for near real-time financial insights.
Develop automation solutions across the enterprise stack using Python, SQL, and Excel.
Apply AI-driven capabilities for predictive insights and intelligent variance analysis.
Create self-service analytics frameworks for stakeholder empowerment.
Establish foundational data models and governance practices for long-term growth.
Benefits
Opportunity to work with cutting-edge AI and machine learning technologies.
Engagement in a dynamic, data-driven environment that supports strategic decision-making.
Potential for professional growth through exposure to modern cloud data platforms.
Collaboration with cross-functional teams to enhance financial insights and analytics.
Focus on building scalable solutions that have a lasting impact on the organization.
Full Job Description
Job Description
ACCOUNTABILITIES & ESSENTIAL FUNCTIONS
Shape and advance the FP&A operating model by designing scalable, automated workflows that support strategic analysis and decision-making.
Design and evolve the finance data layer within the enterprise data ecosystem-transforming ERP and operational data into governed, analysis-ready structures.
Enable faster, more responsive financial insights by building robust data pipelines and transformation logic that support near real-time visibility.
Develop automation solutions across the enterprise stack (Python, SQL, Power Automate, Excel, etc.) to improve efficiency and expand analytical capacity.
Apply AI-driven capabilities within FP&A, including predictive insights, anomaly detection, and intelligent variance analysis to enhance decision support.
Build intuitive, self-service analytics frameworks that empower stakeholders to explore and act on financial data independently.
Establish and scale foundational data models, standards, and governance practices that support long-term consistency and growth.
Implement and manage automation tools end to end, including bot governance, monitoring, and troubleshooting.
Ensure all solutions are well-documented, maintainable, and built for long-term adoption.
Translate complex financial and operational data into clear, executive-ready insights that inform strategic direction.
Strong SQL and Python applied to scalable data and analytics solutions.
Experience designing data models in modern cloud data platforms (Snowflake preferred).
Understanding of financial concepts to align data solutions with business decision needs.
Demonstrated interest in applying AI/ML to enhance analytics and decision-making.
Data, analytics, or cloud certifications a plus (e.g., Snowflake, Microsoft, dbt).
EDUCATION & EXPERIENCE
Bachelor's degree in Data Analytics, Computer Science, Finance, Accounting, AI & Machine Learning, or a related field.
3+ years of experience in analytics engineering, data analysis, or technically focused FP&A.
Prior experience developing and maintaining data pipelines, workflow orchestration processes, and automated job scheduling using modern data engineering and analytics platforms.
Prior experience building data models, automated reporting, or analytics solutions in a finance or business context.
