Data Engineer | Kenility

Data Engineer (POS-203)

About Us:

As a Senior Data Engineer at Kenility, you’ll join a tight-knit family of creative developers, engineers, and designers who strive to develop and deliver the highest quality products into the market.

Technical Requirements:

Bachelor’s degree in Computer Science, Software Engineering, or a related field.
Between one and five years of experience in data engineering or similar technical roles within data-driven environments.
Solid command of data management techniques using both SQL and NoSQL databases, with experience in Redshift considered a plus.
Strong skills in data visualization, particularly with tools such as Power BI and Tableau.
Experience working with Agile frameworks and tools like Jira.
Familiarity with software development processes and cloud-native technologies including S3, EMR (Spark), Lambda, Kinesis, Firehose, Glue, and Terraform.
Programming proficiency in Python and/or Scala, along with a good grasp of infrastructure as code.
Proven ability to design data pipelines and model databases for analytical or feature store purposes, as well as monitor and alert within cloud environments.
Understanding of client-server architectures, including experience with SFTP, APIs, and web scraping.
Experience supporting users of data visualization platforms or teams focused on analytics and data science.
Excellent communication skills and a dedication to advancing professionally in the fields of data engineering and architecture.
Demonstrated success designing scalable, long-term solutions aligned with enterprise needs.
Ability to lead, coach, and mentor team members, including engineers, BI developers, and analysts.
Strong time management abilities and an autonomous, solutions-oriented approach to challenges.
Minimum Upper Intermediate English (B2) or Proficient (C1).

Tasks and Responsibilities:

Design, implement, and support scalable data pipelines and storage systems to power analytics, data science, and operational processes.
Monitor and assess the performance of data infrastructure, applying improvements to boost reliability, speed, and efficiency.
Collaborate closely with cross-functional teams within the Research and Technology departments.
Provide mentorship and technical guidance to fellow engineers, analysts, and BI developers.