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Staff Data Engineer (Analytics)

Afresh Technologies

Join Afresh, a company dedicated to revolutionizing retail grocery analytics. As a Staff Data Engineer, you will lead the development of our analytics platform, collaborating with various teams across the company. Your responsibilities will include improving our data analytics architecture, building extensible dimensional models, evolving data quality and governance processes, and mentoring other engineers. This is a high-impact role with significant growth potential.

Responsibilities

  • Improving, extending, and optimizing the data analytics architecture to provide reliable and accessible data for the suite of data products.
  • Collaborating with stakeholders across the company to understand their data needs, and then building extensible dimensional models, semantic layer metrics, and agentic context and tooling.
  • Evolving existing data quality and data governance processes, and mentoring and up-skilling other engineers.

Requirements

  • Experience working with and extending AI models to produce high quality code and reliable analytics. Experience working on
  • Fluency 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,, Databricks Metrics Views, dbt MetricFlow, etc.)
  • Experience designing and optimizing pipelines of billion+ row datasets
  • 6+ years of experience as a data engineer, analytics engineer, or similar role
  • Experience 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-sharing

Proficiency in dbt

  • A strong sense of ownership and agency — taking initiative to spot problems and solve them without waiting to be told
  • A drive to learn new skills and dive into unfamiliar domains

Pay

USD 168,000 - 250,000