Data Engineer

Responsibilities

• Support QVC and collaborate with an Agile team to build data pipelines and models
• Drive data-driven decision-making and personalization
• Shape both back-end data structures and how insights are delivered
• Design 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 for analytics 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 evolve our approach

• 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
• Knowledge of modern data architecture, application landscapes, and CI/CD tools (e.g., Azure Dev Ops)
• Experience in data warehouse design (e.g., slow changing dimensions, partitioning, indexing) and 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