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Strong employer brand, generic Data Engineer title, mid-level role, and metro context increase competition.
Core data engineering skills transfer across industries, though CX and financial-data context add some domain specificity.
Role requires specific technical skills (SQL, Snowflake, BI) but no explicit years, implying moderate filter strictness.
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Design, build, and maintain scalable, auditable data pipelines consolidating customer experience data from multiple enterprise sources into analysis-ready datasets.
Establish data architecture for customer contact data, surveys, dashboards, and analytics supporting CX and Transactional Experience programmes.
Define secure data-access methods and contribute to a shared data context layer for AI-enabled RIA initiatives.
Experience building and maintaining data pipelines involving customer or CX-related datasets.
Proficiency in SQL and Snowflake for data querying, transformation, and analysis.
Experience with data visualization tools like Tableau or Power BI.
Work Experience Required: Not explicitly mentioned in the JD.
Operates with a delivery-focused approach emphasizing reliable, well-structured, and accurate data outputs.
Experienced in integrating data from multiple enterprise sources for comprehensive user and activity analysis.
Comfortable working collaboratively with cross-functional teams including analytics, CX, marketing, and product to support business and analytics use cases.