Data Science Engineering Manager

Proudly voted a Great Place to Work®, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customercentric companies.

We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we’re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!

Meet the team!

Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic’s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cuttingedge communication and engagement solutions, we want you on our team.

As an Engineering Manager for Data and Analytics, youll lead two teams: Data Engineering Team (Responsible for the architecture, build, and maintenance of a data lake, ETL pipelines, observability, data validation, and the delivery of executivelevel dashboards) and Customer Insights Team (Focused on reporting, building, and maintaining APIs for customerfacing analytical data, both batch and streaming).

The ideal candidate will bring strong technical expertise in modern data technologies, practical experience with data architecture, and the ability to coach and develop highperforming teams. You will play a key role in driving technical excellence and leading initiatives to optimize data infrastructure, reduce costs, and prototype new solutions.

Help us shape the future of communications by:

• Fostering a collaborative and inclusive team culture, encouraging continuous learning and innovation

• Driving technical and professional growth within the team, empowering them to solve complex problems

• Overseeing the architecture and maintenance of the company’s data lake, and drive initiatives to optimize performance and cost

• Exploring and prototyping opensource solutions such as Apache Flink and Apache Pinot for realtime data processing

• Owning the development and optimization of ETL pipelines, data validations, and observability frameworks

• Collaborating with stakeholders to deliver reliable historical reports that empower Clevel dashboards

• Ensuring the delivery of robust APIs that serve customers with batch and streaming analytical data

• Partnering with business units to understand data needs and implement scalable solutions that enable datadriven decisionmaking

• Developing a roadmap for enhancing the data platform, introducing new tools and technologies that align with business goals

• Leading cost optimization efforts through infrastructure enhancements and the evaluation of new technologies

• Driving the data governance, adoption of best practices in data engineering, ensuring scalability, reliability, and highquality data output

• Collaborating crossfunctionally with product, engineering, and business teams to align data initiatives with business objectives

• Communicating technical concepts and project status to Clevel executives and nontechnical stakeholders