We are looking for Data Engineers who:
- Are highly motivated and are excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of product and data.
- Are passionate about truly changing the world and making a big impact by contributing to the development of a significant product that will impact the future of HR globally
- Truly enjoy working in a team and collaborating with others to understand, discover and recommend ways to optimize our product and improve user experience using data
- Are always looking to learn and improve – independent self-learners who love to share what they find
- Have a self-driven work ethic – self-starters who love taking initiative and seeing things through to completion
What you will do:
- Design, develop, monitor and operate data integration pipelines processing millions of records to provide high quality datasets for analytical and machine learning use-cases.
- Build measures of data quality and automated tests of the quality of data powered features.
- Leverage and improve cloud-based (e.g. AWS and GCP) tech stack.
- Consult stakeholders including C-Suite and tech team to build and continuously improve “Single Source of Truth” data products that create value for clients.
- Be a sparring partner to other team members and provide support and guidance to other engineers to help develop their technical capabilities.
You meet all or most of these requirements:
- Bachelor degree required with at least 2 – 3 years experience in a Data Engineer role, preferably with a degree in computer science, electrical engineering, mathematics or any other quantitative field.
- Solid programming skills in Python.
- Experience in performing data analysis with optimized SQL.
- Proficient knowledge in developing data pipelines with Apache Beam for cloud-based analytics is a plus.
- Knowledge of workflow management tools such as Apache Airflow.
- Hands-on experience in cloud technologies (AWS, GCP preferred) and container technology tools (Docker).
- Experience in all the steps of the engineering process, including testing, continuous integration/continuous delivery, automated deployment and monitoring.
- Strong analytical and problem-solving skills, with the ability to comprehend and troubleshoot from a data & design point of view, and propose sustainable solutions
- Able to own mistakes, reflect and take feedback with maturity and a willingness to improve.