About Dialpad
Dialpad is the leading Ai-powered customer communications platform, transforming how businesses communicate with their customers. More than 50,000 companies around the globe — including Netflix, RE/MAX, Uber, Randstad, and Tractor Supply — rely on Dialpad to build stronger customer connections using real-time, Ai-driven insights. Visit dialpad.com to learn more.
Being a Dialer
At Dialpad, you’ll be part of a collaborative team working toward our shared mission of making our customers and their employees wildly successful. We believe that every conversation matters, and we're elevating each one with a platform that drives real-time insights and automation for our customers.
We thrive on continuous evolution, where every employee leverages industry-leading Ai to constantly refine our platform and our own skills. We seek individuals who not only meet our high standards but go beyond them. Our ambition is significant, and achieving it requires a team that operates at the highest level. We look for individuals who are not just ambitious but who also possess the traits that are fundamental to our success: Scrappy, Curious, Optimistic, Persistent, and Empathetic.
Your role
As an Analytics Engineer, you will collaborate with business stakeholders across various departments to effectively leverage big data and provide accurate, actionable insights that address key business questions. This role is based in Argentina and reports to the Senior Director of Data Analytics in the US. The candidate must be available to work during US overlapping hours (12 NN to 8 PM ART) and be willing to travel occasionally.
Dialpad’s data team acts as a centralized hub, supporting the analytics and business intelligence needs of all global departments such as Finance, Product, Engineering, Customer Support, Marketing, Legal, HR, and Sales. The team is responsible for data ingestion, ensuring data quality, managing data engineering, and delivering business analytics services, including report automation, as well as descriptive and predictive analytics. Dialpad’s data team operates from five global hubs located in the US, Canada, Argentina, India, and the Philippines.
What you’ll do
- Collaborate with Growth and Marketing teams to analyze data from multiple sources, delivering clear data insights that enable informed, strategic decisions.
- Initially support the Growth and Marketing teams, with flexibility to assist other departments as needs arise.
- Promote self-serve analytics throughout the organization by developing a comprehensive suite of fully automated, accurate, and reliable dashboards.
- Develop detailed data model requirements and document business logic for the Data Engineering team to create curated datasets for report automation and analysis.
- Perform statistical analysis, hypothesis testing, and build predictive machine learning models to optimize costs, forecast business outcomes, enhance product experiences, and drive business growth.
- Collaborate with external teams to improve the quality and usability of our internal data.
- Proactively monitor business performance through automated dashboards and ad-hoc analysis, providing leadership with actionable insights.
- Collaborate with data analysts and engineers across the organization to improve best practices and enhance data utilization and processes.
- Identify opportunities for continuous process improvement and cost optimization.
Skills you’ll bring
- 5+ years of advanced data analytics experience using big data.
- Experience working directly with business stakeholders to define requirements, drive analytics, and deliver effective insights.
- Experience collaborating with Data Engineers, Business Analysts, and Team Leads, with a demonstrated track record of successfully working with offshore teams and delivering complex projects on time.
- Advanced SQL development skills for data exploration and analysis.
- Strong analytical and problem-solving skills.
- Experience building effective visualizations and dashboard automations in an advanced BI tool like Tableau (preferred), PowerBI, DOMO, or Looker.
- Bachelor’s degree in a technical or business field.
- Expertise in product and financial data analysis.
- Experience working in a SaaS-based technology company.
- Experience in building and training machine learning models for business analysis use cases.
- Proficiency in Python for data exploration and analysis.
- Hands-on experience with Agile Software Development methodologies and tools like Jira.
- Working experience in cloud-based data platforms like GCP, AWS, or Azure.
We believe in investing in our people. Dialpad offers competitive benefits and perks, alongside a robust training program that helps you reach your full potential. We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection. Our exceptional culture, recognized repeatedly as a certified Great Place to Work, ensures every employee feels valued and empowered to contribute to our collective success.
Don’t meet every single requirement? If you’re excited about this role and you possess the fundamental traits, the drive, and strong ambition we seek, but your experience doesn’t satisfy every qualification, we encourage you to apply.
Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.
Top Skills
What We Do
Dialpad is a cloud-based business phone system that turns conversations into opportunities and helps global teams make smarter calls--anywhere, anytime. We bring simplicity to the professional phone experience and some of the world’s most innovative companies use our platform. Dialpad's products span video meetings, cloud call centers, sales coaching and dialers and enterprise phone systems--and are all infused with the latest AI technologies to help every business make smarter calls. Customers include WeWork, Uber, Motorola Solutions, Domo and Xero. Investors include Amasia, Andreessen Horowitz, Felicis Ventures, GV, ICONIQ Capital, Salesforce Ventures, Scale Venture Partners, Section 32, Softbank and Work-Bench.
