Data Engineer building high-quality data pipelines and analytics for QVC's social commerce platform. Collaborating with Agile teams to extract insights and enhance data-driven applications.
Responsibilities
Design and maintain data architecture, models, APIs, and pipelines aligned with data architecture principles and team goals
Solve complex data challenges to deliver insights that drive outcomes
Create data products for analytics and data science teams to improve their productivity and insights
Lead the evaluation, implementation, and deployment of new tools and processes for analytic data engineering
Develop and deliver plans on analytic data engineering capabilities and standards
Partner with product teams and solution architects to develop scalable, reliable technical architectures
Mentor peers through code reviews, collaboration, and technical coaching
Explore and learn about machine learning, data science, AI, and personalization technologies to continuously evolve our approach
Requirements
Bachelor's degree in Computer Science or related field, or equivalent experience
4+ years of software development and design experience with emphasis on data warehousing, ETL, and database design
Experience developing data engineering processes and SQL proficiency
Experience using Azure tools (Databricks, Data Factory, Delta Lake, Synapse, ADLS, PySpark, SQL Server, Databricks Notebooks)
Experience transforming, cleansing, and ensuring quality of large-scale data sets
Understanding of modern data architecture, application landscapes, and CI/CD automation tools such as Azure DevOps
Experience in data warehouse design techniques (slow changing dimensions, partitioning, indexing) and applying AI-driven personalization models
Familiarity with Agile (Scrum), distributed systems, and 24×7 production environments
Understanding of compliance, regulations, and data governance in tech environments
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