Analyze large datasets to develop actionable customer experience insights and create compelling presentation materials for clients. Support client engagement managers in delivering insights, training clients on the platform, and managing multiple workstreams.
Design, build, and optimize scalable ETL/ELT data pipelines using Databricks, Python, and SQL. Collaborate with cross-functional teams to implement cloud-based data architectures and ensure data quality and performance.
The role involves owning data workstreams to develop client-ready visualization dashboards and managing end-to-end benchmarking survey instruments. It also requires providing technical support to subscription customers and collaborating with stakeholders to translate complex technical concepts into actionable insights.
Design, build, and optimize scalable ETL/ELT data pipelines using Databricks, Python, and SQL. Develop client-ready visualization dashboards in Tableau and support data preparation for benchmarking surveys.
Develop and deploy AI solutions ranging from classical machine learning models to advanced Generative AI and multi-agent systems. Own the end-to-end data science lifecycle, including problem framing, experimentation, production deployment, and monitoring.
The Data Engineer will design, build, and optimize ETL/ELT workflows and develop scalable data pipelines. They will also collaborate with cross-functional teams to deliver impactful data solutions.
