Data Engineer

Key Responsibilities

• Shape and develop data pipelines, models, source system integrations, and analyses.
• Perform data transformations from a big data processing perspective using PySpark, SQL, and other scripting languages to handle high volumes of data
• Tackle challenging and complex tasks, such as ingesting data from diverse sources, formats, and technologies, to develop, test, and maintain architectures and large-scale data processing systems and workflows, or to make high volumes of data available for further processing, extraction, and analysis
• Act as a bridge between data sources and data consumers, including analysts, data scientists, and decision-makers, ensuring seamless data flow and usability.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field
• Proven experience as a Data Engineer or in a similar role, with a minimum of 2 years of experience
• Proficiency in SQL, Python, and PySpark development
• Background in agile development practices and experience with CI/CD
• Excellent quantitative and analytical skills, with the ability to interpret business challenges from non-technical individuals and offer appropriate data solutions
• Ability to communicate complex technical topics to a non-technical audience
• Creative problem-solving skills and great attention to detail
• Fluent in English

Bonus points for:

• Experience with Git workflow and version control
• Relevant experience with data engineering in an Azure and/or Databricks environment
• Strong SQL abilities
• Experience in building robust, scalable, high-quality data products

What’s next?