Software Engineer

About the team

Our Data Analysis and QA team works alongside the Data Annotation team to support the Ai teams, working on projects on cutting-edge Automatic Speech Recognition(ASR), Natural Language Processing(NLP) and Computer Vision(CV). We take care of the complex business and product logic as well as making sure the data follows our security and privacy standards letting our applied scientists focus on model development. We help the NLP team to launch and enhance DialpadGPT, our in-house LLM specifically designed for the domain of business communication. 

We work closely with the Product team to help them understand how users interact with our Ai product using data analysis. 

We also build data pipelines and infrastructure and adopt software engineering best practices.

We are a group of engineers who enjoy writing reports to tell the stories behind the data, which often spin up new data science ideas and help businesses make better decisions.

Your role

As a software engineer, you’ll be an integral part of our data analysis and QA team, supporting ASR and NLP teams for their data needs. You will own our internal package for dataset management and anonymization. You’ll work closely with our Ai Engineering team to build and maintain toolings for data science projects. You will help the team with various technical issues. You’ll be actively looking for opportunities to improve the team’s productivity and workflow through automation and process optimization. You will work with QA team to implement automated QA. 

This position reports to the manager of the data analysis and QA team and has the opportunity to be based in our Vancouver Office. 

What you’ll do 

• You will own our internal library for dataset management and other data tooling packages 
• You will build and maintain data pipelines on Kubeflow
• You will implement rigorous testing for our data pipelines and SQL queries 
• You will work closely with Ai Engineering team to build toolings for data science projects 
• You will implement automation and processes to improve our workflow 
• You will share the ownership of the DBT core infrastructure with AI Engineering
• You will create and maintain dashboards (Tableau) and data pipelines (DBT) that help drive product and business decisions
• You will contribute to our continuous efforts to enforce data privacy and compliance 
• You will collaborate with cross-functional teams, including Ai, engineering and product team

Skills you’ll bring 

• Bachelor’s or Master’s degree in Computer Science, Software Engineering or related fields.
• 2 - 4 years of working  experience with software engineering or data engineering project 
• 2 - 4 years of experience with Python, preferably building libraries or web applications 
• 2 -4 years of experience with SQL, able to optimize complex SQL queries and build data pipelines 
• Experience working with GCP including storage, BigQuery, Compute, Kubernetes or similar.
• Experience with version control systems such as Git. 
• Experience with CI/CD and familiarity with containerization using Docker or similar.
• Familiarity with DBT Cloud (bonus: DBT Core)
• Familiarity with BI tools such as Tableau 
• Strong attention to detail, with a focus on data accuracy, quality, and integrity.
• Strong problem-solving and analytical abilities, with the capacity to handle complex technical and analytical problems.
• Excellent communication and collaboration skills to effectively work in a multi-disciplinary team.
• Familiarity with version control tools like Git for collaborative projects.

Dialpad benefits and perks

Benefits, time-off, and wellness

An apple a day keeps the doctor away—and it doesn’t hurt that we offer flexible time off and great options for medical, dental, and vision plans for all employees. Along with that, employees also receive a monthly stipend to help cover your cell phone bill, home internet bill, and we reimburse for gym membership costs, a variety of wellness events, and more!

Professional development

Dialpad offers reimbursement for expenses related to professional development, up to an annual limit per calendar year.