Staff Data Engineer (Analytics)

Afresh Technologies; San Francisco (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health plans

Parental leave

Equity

401k matching

Flexible vacation

Professional development

Work from home stipend

Job summary

Afresh Technologies is seeking a Staff Data Engineer to own and evolve the analytics platform for internal and customer analytics.

You will advance data models, pipelines, and governance while mentoring engineers and partnering with product, data science, and operations teams to deliver reliable, AI-enabled insights.

Qualifications

• 6+ years of experience as a data engineer, analytics engineer, or similar role.
• Fluency in SQL, dimensional modeling, and data warehouse design.
• Experience with cloud data warehouses (Databricks, Snowflake, BigQuery).
• Experience with modern semantic layers: LookML, Cube.dev, Databricks Metrics Views, dbt MetricFlow.
• Experience designing and optimizing pipelines of billion+ row datasets.
• Experience with orchestration tools: Airflow/Astronomer, Dagster.

Responsibilities

• Improve, extend, and optimize our data analytics architecture to provide reliable data for our product suite.
• Collaborate with stakeholders to build extensible dimensional models, semantic metrics, and AI-enabled insights tooling.
• Evolve data quality and governance processes to ensure reliable analytics.
• Mentor and up-skill other engineers; own high-impact projects with broad scope.

Skills

SQL

Dimensional modeling

Data warehouse design

dbt

LookML

Airflow

Dagster

Tools

Databricks

Snowflake

BigQuery

Databricks Metrics Views

Cube.dev

dbt MetricFlow

Job description

• At Afresh, we're building data products to define the future of retail grocery analytics. The nerve center of those products is our analytics platform, and as a Staff Data Engineer on the Data Science and Analytics team, you'll be the technical leader of that platform
• Our growing suite of data products range from standardized reports to AI-driven insight engines and agentic analytics tools. They let our customers understand what's happening in their stores and empower them to reduce food waste. All of these products require a reliable platform of well-modeled data, clearly-defined metrics, and extensive metadata and context
• This platform is also used by teams across the company to ensure customer success and improve our core products. The Data Science and Analytics team collaborates closely with every team in the company, helping them build products and make decisions with data. You will regularly interact with data engineers, product engineers, product managers, data scientists, and operations specialists
• As a Staff Data Engineer on the Data Science team, you will own the development of our analytics platform. You'll evolve our data models, solidify our pipelines, and establish data governance patterns to serve our internal- and customer-facing analytics needs. Some of your responsibilities will include:
• Improving, extending, and optimizing our data analytics architecture to provide reliable and accessible data for our suite of data products
• Collaborating with stakeholders across the company to understand their data needs, and then build extensible dimensional models, semantic layer metrics, and agentic context and tooling that will allow for consistent and reliable AI-assisted insights
• Evolving our existing data quality and data governance processes; and
• Mentoring and up-skilling other engineers
• This is a high-impact role with ownership of highly visible projects and a lot of room to grow in your scope

Benefits

• Comprehensive health plans
• Generous parental leave
• Equity packages
• 401k matching
• Flexible vacation policy
• Professional development program
• Work from home stipend

Experience working with and extending AI models to produce high quality code and reliable analytics. Experience working onFluency in advanced concepts in SQL, dimensional modeling, and data warehouse design; experience with Cloud Data Warehouse platforms (Databricks, Snowflake, BigQuery, etc.)Experience with modern semantic layers: LookML, Cube.dev, Databricks Metrics Views, dbt MetricFlow, etc.)Experience designing and optimizing pipelines of billion+ row datasets6+ years of experience as a data engineer, analytics engineer, or similar roleExperience with orchestration tools (Airflow/Astronomer, Dagster, or similar)Exceptional communication and leadership skills, with a proven ability to facilitate cross-team and cross-functional collaboration and information-sharingProficiency in dbtA strong sense of ownership and agency - taking initiative to spot problems and solve them without waiting to be toldA drive to learn new skills and dive into unfamiliar domains