Senior Finance Analytics Developer

Texas Capital•Dallas, NC

About The Position

Own analytics that directly influence Finance strategy. Partner with leaders to translate business needs into insights, and build toward AI- and advanced analytics–driven solutions that accelerate impact. You’ll operate independently, collaborate as a technical peer with engineers and fellow BI analysts, and see your work drive real decisions. This role is ideal for someone with 3-5+ years of experience who wants end-to-end ownership of analytical problems and brings the technical foundation and curiosity to grow in AI-powered analytics. We're building the next generation of Finance analytics, moving from static reporting to dynamic, AI-assisted insights that the CFO organization relies on daily. This role sits at that center: you'll maintain our existing financial data foundation while designing and deploying new analytics products that drive decisions on FP&A, liquidity management, and financial performance, increasingly with AI-powered workflows.

Requirements

3-5+ years of hands-on experience in analytics or data science
Proficiency in SQL and Python; comfortable writing production-quality, version-controlled code
Familiarity with dimensional modeling and cloud data warehouses; Snowflake experience is a plus
Hands-on experience building dashboards in at least one modern BI tool (Power BI, Sigma, Looker, or similar)
Able to communicate technical work clearly to non-technical audiences
Bachelor's degree in a quantitative field (Computer Science, Data Science, Statistics, Engineering, or related) required

Nice To Haves

Foundational knowledge of AI and LLMs: basic understanding of how language models work, prompt engineering concepts, and API integration
Background in financial reporting, FP&A, or related Finance operations
Experience with Streamlit or Posit for analytical applications
Comfortable with code reviews, version control, and iterative delivery
Demonstrated eagerness to learn AI development with a growth mindset

Responsibilities

Write clean, well-documented SQL and Python that others can maintain and build on; learn to apply agentic AI to financial analytics workflows, automating insight generation, explaining anomalies in data, and accelerating report narratives
Build dashboards and data applications Finance teams actually use, and improve them based on real feedback
Validate data accuracy against business expectations and collaborate with data engineering and our data governance program to identify and resolve data quality issues
Translate analytical findings into clear narratives for Finance leadership, including the CFO and other senior stakeholders
Collaborate with senior analytics developers on AI integration: help design and test LLM-powered analytics workflows, learning prompt engineering, tool use, and multi-step reasoning for financial analysis
Proactively spot gaps in existing analytics and propose solutions, including where AI tooling could unlock new capabilities
Participate in code reviews and communities of practice to share learnings and contribute to the growing AI analytics practice within the organization