Sr Finance Analytics Engineer

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.

SKILLS & CERTIFICATIONS

• Skill evaluation: Behavioral (80%); Coding & Technical Challenges (80%)
• 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.