Your Impact: As a Lead Financial Analyst, you will play a pivotal role in transforming how data is structured, accessed, and leveraged across Sales, Marketing, and Finance. Reporting to the Sr. Director, Corporate Revenue Operations, this role bridges business strategy with advanced analytics and scalable data solutions.
In this role, you will move beyond traditional analysis to design and build the data environment, automation frameworks, and analytical tools that power decision-making. You will act as both a strategic advisor and a hands-on builder-creating the infrastructure and logic that enable AI-driven insights, automation, and scalable reporting.
This position requires a strong blend of business acumen, systems thinking, and technical expertise to deliver not just insights-but the platforms that generate them.
What the role offers: Data Environment & Systems Development
- Design, build, and manage scalable data environments that consolidate data across Sales and Finance
- Create and maintain structured datasets and data models that serve as the foundation for reporting, analytics, and automation.
- Develop and optimize data pipelines and workflows to ensure reliable, timely, and accurate data availability.
- Establish best practices for data structure, documentation, and quality to enable scalability and reuse.
Automation, Scripting & Analytical Tooling
- Maintain and develop Python-based scripts and workflows to automate reporting, data transformation, and recurring analysis.
- Build reusable analytical frameworks that reduce manual effort and standardize outputs across the team.
- Evaluate, validate, and continuously improve data outputs and logic to ensure accuracy and usability.
- Support the development of AI and advanced analytics capabilities by creating clean, well-structured datasets.
Business Insights & Metric Development
- Partner with stakeholders in Sales, Marketing, and Finance to define, refine, and operationalize KPIs and business metrics.
- Act as a subject matter expert on data structure, access, and interpretation.
- Ensure alignment between business definitions and underlying data structures.
- Translate complex data outputs into clear, actionable insights for leadership.
- Shift reporting from static outputs to scalable, automated, and insight-driven solutions.
What you need to succeed: - 6-8+ years of experience in analytics, data science, data engineering, or related roles in a fast-paced technology environment.
- Strong programming skills in Python, with experience building scripts, workflows, or automation solutions.
- Advanced SQL skills and experience working with large, complex datasets.
- Proven experience designing or working with data models, databases, or consolidated data environments.
- Experience building or optimizing data pipelines, reporting frameworks, or analytical tools.
- Familiarity with data quality, governance, and structuring best practices.
- Ability to move between technical execution and business problem-solving.
- Strong analytical, problem-solving, and systems-thinking skills.
- Excellent communication skills with the ability to simplify complex data concepts.
- Degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, or related field.
Compensation: At OpenText, we offer a thoughtfully designed benefits package that supports your physical, emotional, and financial wellbeing. A summary of those benefits can be found on our Why Join Us page. As you move through the hiring process, we're happy to provide more details about our compensation programs, including variable and commission compensation opportunities for eligible roles, vacation entitlement, and paid time off.
Salary Range: $8,6800 - $130,200; Depending on the candidate's education, experience, skills, geographical location, and alignment with internal equity and external market, actual salary may vary and be higher or lower than the range posted.
AI Usage Disclosure: As part of our commitment to transparency, we use artificial intelligence (AI) tools to assist in various stages of our recruitment process, including resume screening, candidate matching, interview scheduling, and communications. These tools are designed to improve efficiency, reduce bias, and enhance candidate experience. All decisions regarding hiring are made by qualified human professionals, and we continuously monitor our AI systems to ensure fairness and compliance with applicable regulations.
