Staff Data Engineer — Lead Analytics Platform & AI Insights

afresh; United States; Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health & dental

Equity for US employees

401(k) match

Home office stipend

Coworking Wallets

Professional development budget

Wellbeing stipend

Job summary

Afresh is seeking a Staff Data Engineer to lead the Data Science and Analytics platform. You will shape data models and pipelines that power AI-driven insights, reports, and analytics across the company and for customers.

The role emphasizes scalable data architecture and collaboration with product, data science, and operations teams. You will mentor peers, extend data quality and governance, and help drive high-impact decisions with data.

Qualifications

• 6+ years of experience as a data engineer, analytics engineer, or similar role.
• Exceptional communication and leadership skills, with cross-team collaboration.
• A drive to learn new skills and dive into unfamiliar domains.
• A strong sense of ownership—solving problems proactively.
• Fluency in SQL, dimensional modeling, and data warehouse design; cloud DW platforms.
• Proficiency in dbt.
• Experience with orchestration tools (Airflow/Astronomer, Dagster, or similar).
• Experience with modern semantic layers: LookML, Cube.dev, Databricks Metrics Views, dbt MetricFlow.

Responsibilities

• Own the development of our analytics platform and evolve data models and pipelines.
• Establish data governance patterns to serve internal and customer analytics needs.
• Collaborate with stakeholders to translate data needs into extensible models and metrics.
• Mentor and up-skill other engineers.

Skills

SQL

Dimensional modeling

Data warehouse design

dbt

Airflow

LookML

Databricks

Snowflake

BigQuery

Cloud DW platforms

Tools

Airflow

Dagster

Astronomer

Databricks

Snowflake

BigQuery

Job description

Afresh is seeking a Staff Data Engineer to lead the Data Science and Analytics platform. You will shape data models and pipelines that power AI-driven insights, reports, and analytics across the company and for customers.

The role emphasizes scalable data architecture and collaboration with product, data science, and operations teams. You will mentor peers, extend data quality and governance, and help drive high-impact decisions with data.