Staff Data Engineer at Afresh

Afresh is seeking a Staff Data Engineer to enhance customer data integration and processing. The role involves designing and implementing ETLs for large data volumes and developing tools to accelerate customer integrations. The Staff Data Engineer will collaborate with product, engineering, and go-to-market teams to create data solutions for new products. They will identify optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. They will also investigate and implement new technologies into the data platform.Responsibilities include:

• Building tools and frameworks to streamline customer integrations.
• Creating robust ETLs in PySpark and DBT.
• Collaborating with cross-functional teams to design data solutions.
• Identifying and implementing optimizations to improve scalability.
• Solving real-world data quality challenges.
• Investigating and implementing new technologies.
• Supporting team members through mentorship and feedback.

Requirements:

• Significant experience designing and maintaining ETLs for large-scale datasets.
• Proficiency with Python, PySpark, SQL, and platforms like Databricks, Snowflake, or DBT.
• Strong problem-solving skills.
• Focus on practical outcomes.
• Experience with complex, unclean datasets.
• Ability to identify areas for tooling or automation.
• Excellent communication skills.
• Proven leadership in technical projects.

Afresh offers:

• Opportunity to work on real-world problems that impact customers.
• A collaborative, supportive team environment.
• The chance to use cutting-edge tools and platforms.