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Follow →Chip is seeking a Senior Data Engineer to co‑own the data platform architecture, guiding ingestion, modeling and the semantic layer. You’ll mentor engineers, set governance standards, and ensure scalable, secure data pipelines across sources.
You will apply Databricks best practices, drive medallion architecture maturity, and enable self‑service access for downstream teams while maintaining strong collaboration with the Analytics Engineer.
Senior Data Engineer builds and scales Chip’s data platform using Databricks, Python, PySpark, and SQL to enable a data-driven fintech wealth app.
Designs and maintains scalable cloud-native data pipelines and platforms for a global telco SaaS provider, using Python, Spark, Kafka, and cloud data warehouses to support analytics and operations across multiple markets.
Design and build scalable cloud-native data pipelines and platforms (batch/streaming) using Python, Spark, Kafka, and cloud data warehouses to power analytics and ML across global telco markets.
Designs and presents scalable Big Data Analytics solutions using Python and cloud technologies to enterprise clients.
The Senior Data Engineer will lead data engineering standards, architecture, and governance while mentoring junior staff. The role focuses on building scalable cloud data platforms using Azure technologies, SQL, and Spark.
Own and improve a Databricks-based data platform that powers BI and analytics, writing notebooks, modeling data layers, and mentoring teammates.