Sr Finance Analytics Engineer

Mouser•Mansfield, TX

About The Position

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.

Requirements

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.
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.

Nice To Haves

Data, analytics, or cloud certifications a plus (e.g., Snowflake, Microsoft, dbt).

Responsibilities

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.