Senior Data Engineer
New
A
AfreshGrocery AI Platform
AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WIFull-TimeSenior
Salary137000 - 185000 CAD per year
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Job Details
- Experience
- Significant experience
- Required Skills
- PythonSQLETLSnowflakedbtDatabricksPySpark
Requirements
- Significant experience designing and maintaining ETLs that process large-scale datasets.
- Proficiency with Python, PySpark, SQL.
- Experience working on platforms/tools like Databricks, Snowflake, or DBT.
- Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
- A focus on practical outcomes—skilled at balancing technical rigor with the need to get things done.
- Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
- A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
- Excellent communication skills—able to explain ideas clearly to both technical and non-technical audiences.
- Proven leadership in technical projects, with a willingness to mentor and help others grow.
Responsibilities
- Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data.
- Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
- Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs.
- Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
- Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
- Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
- Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.
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