Senior Data Engineer at Afresh

Ontario, Canada

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Grocery Retail, Food TechnologyIndustries

Requirements

Significant experience designing and maintaining ETLs that process large-scale datasets
Proficiency with Python, PySpark, SQL, and 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—you're 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—you’re able to explain your 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

Skills

Key technologies and capabilities for this role

PySparkDBTETLData PipelinesData IntegrationBig Data ProcessingData QualityScalability

Questions & Answers

Common questions about this position

What technical skills are required for the Senior Data Engineer role?

The role requires significant experience designing and maintaining ETLs that process large-scale datasets, proficiency with Python, PySpark, SQL, and experience with platforms/tools like Databricks, Snowflake, or DBT.

What does a great fit candidate look like for this position?

A great fit has strong problem-solving skills, ability to work with ambiguous requirements, focus on practical outcomes, experience with complex unclean datasets, and a knack for identifying tooling or automation opportunities.

Is this Senior Data Engineer position remote?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What does the team collaboration look like in this role?

You'll collaborate with product, engineering, and go-to-market teams to design and deliver data solutions, support team members by mentoring engineers, leading technical discussions, and providing feedback.

Afresh

AI solutions for fresh food inventory management

About Afresh

Afresh Technologies provides solutions for grocery retailers to improve their inventory management in the fresh food supply chain. Their platform uses machine learning algorithms to help retailers reduce food waste and increase profitability by optimizing how they manage their stock. Retailers subscribe to Afresh's service, gaining access to its features and potentially additional services like data analytics and consulting. What sets Afresh apart from competitors is its specific focus on the fresh food sector and its commitment to helping retailers meet consumer demand while minimizing waste. The company's goal is to enhance the efficiency of fresh food management in retail.

33 New Montgomery St, San Francisco, CA 94105, USAHeadquarters

2017Year Founded

$147.8MTotal Funding

SERIES_BCompany Stage

Food & Agriculture, Enterprise Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Comprehensive health plans

Competitive compensation

Generous parental leave

Equity packages

401(k) matching

Flexible vacation policy

Monthly grocery stipend

Professional development program

Risks

Tech giants entering AI supply chain space threaten Afresh's market share.

AI advancements may render Afresh's platform obsolete if not updated.

Data privacy regulations could hinder Afresh's data collection and usage.

Differentiation

Afresh uses AI to optimize fresh produce inventory management for retailers.

The platform minimizes waste and maximizes freshness through advanced machine learning.

Afresh offers a subscription model, providing continuous access to its AI-driven solutions.

Upsides

Growing demand for AI in supply chain boosts Afresh's market potential.

Retailers seek sustainable solutions, aligning with Afresh's waste-reduction mission.

Omnichannel retailing increases need for sophisticated inventory systems like Afresh's.

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