Business Intelligence Engineer
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Job Description
Business Intelligence Engineer at DataRobot developing dashboards and driving analytics for SaaS business processes. Collaborating with business leaders for operational insights and decision-making based on data.
Responsibilities:
- Work with business leaders to implement best practices for measuring business processes, define critical KPIs and metrics, manage performance, and create operational rigor.
- Drive the framework to measure marketing, demand gen, customer success, and financial processes using industry-standard metrics, e.g., bookings/ARR, financial forecast, Plan vs. actuals, conduct rigorous exploratory data analysis, and create executive-facing dashboards that drive decision-making and actions.
- Communicate insights through reports, dashboards, and advanced analytics, and build narratives and strategic recommendations to support key decision-making.
- Create a playbook to drive quarter-end close activities, monthly/quarterly financial forecasting
- Influence process teams to address process gaps that result in data issues and drive process improvements.
- Work with data engineering/data science team to establish data sources that serve teams' business needs, identifying and advocating for process improvements and industry best practices (e.g., standard metric definitions).
- Synthesize large volumes of data with attention to granular details, building certified data sources, and addressing data quality issues and process gaps.
- Support multiple projects at the same time in a fast-paced, results-oriented environment.
- Drive automation of repetitive processes and build self-serve tools (e.g., Tableau Dashboards) to empower product and business stakeholders.
Requirements:
- 4-6 years of experience
- Fluent in English
- Understanding of GTM and post-sales business processes in a SaaS business.
- Experience building SaaS metrics such as Renewals, Churn, Customer Health Scores, Retention Rates, and ARR is required.
- Experience with data modeling and data transformation tools like DBT.
- Strong understanding of B2B SaaS metrics and business processes.
- Fluent in advanced analytical SQL, Excel, and visualization tools such as Tableau, Looker, or Qlikview; experience with a statistical programming language like R or Python preferred
- Prior work experience in a business analytics space would be highly valued.
- Analytical and problem-solving experience, exposure to large-scale data warehouses
- Deep understanding of complex data models, BI methodologies, Data Architecture principles, Master data, and metadata
- Understanding of operational processes, systems, and data in multiple areas of Sales and operations, such as forecasting, Pipeline management, Account management, Sales performance, etc.
- Entrepreneurial self-starter.
- Thrive in a fast-paced environment and independently capable of seeking information, corralling resources, and delivering results without waiting for direction.
- Thrive on combining rigorous data-driven analysis, strong business and product judgment, and an ability to work well across teams.
- Comfortable handling sometimes ambiguously defined problems, developing creative solutions, and delivering against aggressive timelines
- Consistent track record of initiating and leading cross-functional and cross-organizational projects, building relationships with partners, and influencing decision-makers.
- Strong verbal and written communication skills.
- A data-driven mindset with a degree in any quantitative discipline, such as Engineering, Computer Science, Economics, Statistics, or Mathematics.
Benefits:
- Medical, Dental & Vision Insurance
- Flexible Time Off Program
- Paid Holidays
- Paid Parental Leave
- Global Employee Assistance Program (EAP) and more!
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