01Overview
5+ years of experience in data engineering, backend engineering, or a related discipline
Understand business and define success metrics. Exposure to analytics on conversational support.
Strong proficiency in SQL and Python for data transformation and pipeline development
Deep hands-on experience with Snowflake, BigQuery, or similar cloud data warehouses
Expertise in ETL/ELT pipeline development using tools such as dbt, Airflow, or Apache Spark
Hands-on experience with Apache Airflow for pipeline orchestration, scheduling, and workflow management
Proficiency in working with Data Labs or similar collaborative data experimentation platforms to support analytics and data science teams
Strong understanding of data modelling principles, including dimensional modelling and schema design
Experience with Git, CI/CD workflows, and writing clean, production-quality code
Proven experience in designing and implementing semantic layers that abstract complexity from underlying data marts, empowering analysts with a single, consistent, and performant view of enterprise data
Ability to work independently with minimal oversight and strong ownership mindset
Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders .
