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About the role
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 .
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