Sr Software Engineer - Enterprise Data Platform & Customer Data Platform

Senior Software Data Engineer

At Five Below our growth is a result of the people who embrace our purpose: We know life is way better when you are free to Let Go & Have Fun in an amazing experience, filled with unlimited possibilities, priced so low, you can always say yes to the newest, coolest stuff! Just ask any of our over 20,000 associates who work at Five Below and they'll tell you there's no other place like it. It all starts with our purpose and then, The Five Below Way, which is our values and behaviors that each and every associate believes in.

It's all about culture at Five Below, making this a place that can inspire you as much as you inspire us with big ideas, super energy, passion, and the ability to make the workplace a WOWplace!

Position Overview We are seeking a Senior Software Data Engineer to lead the design, development, and optimization of our Enterprise Data Platform (EDP) and Customer Data Platform (CDP) using Azure and Azure Databricks. This role will architect metadata-driven data solutions, lead a team of data engineers, and collaborate with cross-functional stakeholders to deliver scalable, secure, and efficient data infrastructure.

Key Responsibilities Leadership: Mentor and lead a team of data engineers, fostering innovation, collaboration, and technical excellence while overseeing project delivery and resource allocation. Enterprise Data Platform Development: Architect and maintain a robust EDP on Azure to centralize data assets, enabling enterprise-wide analytics, reporting, and insights generation. Customer Data Platform Development: Design and implement a CDP on Azure to unify customer data, enabling personalized experiences, segmentation, and advanced analytics. Metadata-Driven Frameworks: Build scalable, metadata-driven frameworks in Azure Databricks for data ingestion, transformation, and orchestration, ensuring flexibility and reusability. Data Pipelines: Develop and optimize end-to-end data pipelines using Azure Databricks, Spark, and Apache Kafka for batch and real-time processing to support EDP and CDP use cases. Azure Cloud Integration: Deploy and manage cloud-native data solutions on Azure, integrating seamlessly with Azure Databricks, Azure Data Lake Storage and other Azure services. Data Governance & Compliance: Implement metadata management, data cataloging, and lineage tracking using Databricks Catalog to ensure data quality, security, and regulatory compliance (e.g., GDPR, CCPA). Database Management: Design and manage scalable databases (e.g., lakebase) for efficient storage, retrieval, and querying of enterprise and customer data. Orchestration: Leverage Apache Airflow Workflows to orchestrate complex data pipelines reliably and at scale. Performance Optimization: Enhance pipeline performance, query efficiency, and cost optimization for large-scale data processing in Azure environments. Collaboration: Partner with product managers, data scientists, analysts, and business stakeholders to align data solutions with enterprise and customer goals. Innovation: Stay abreast of emerging Azure data technologies and trends, driving adoption of best practices and tools to enhance EDP and CDP capabilities.

Required Qualifications Experience: 8-10+ years in data engineering, with 4+ years focused on enterprise-scale data platforms and/or customer data platforms, including 3+ years in a lead or senior role managing teams. Leadership: Proven ability to lead, mentor, and inspire data engineering teams, with experience in agile project management and cross-functional collaboration. Azure Databricks Expertise: Advanced proficiency in Azure Databricks, Delta Lake, Spark, and Databricks Workflows for building scalable data solutions. Big Data Technologies: Deep expertise in Spark, Apache Kafka, and related big data technologies for large-scale and real-time data processing. Database Management: Strong skills in designing and managing MongoDB, Delta Lake, or similar databases for enterprise and customer data use cases. Orchestration: Hands-on experience with Apache Airflow workflows for pipeline orchestration. Metadata & Governance: Expertise in metadata management, data cataloging, and lineage tools to ensure data quality and compliance. Programming Skills: Proficient in Python, PySpark, Spark SQL, and SQL for developing robust data pipelines and transformations. SQL Mastery: Advanced skills in query optimization and performance tuning for large-scale datasets in Azure data lakes and warehouses. Data Modeling: Strong knowledge of data modeling techniques, including star schema, Snowflake schema, and data lake/warehouse architectures. Problem-Solving: Exceptional analytical skills with a solution-oriented mindset to tackle complex data challenges. Communication: Outstanding verbal and written communication skills to collaborate with technical and non-technical stakeholders.

Preferred Qualifications Experience building or managing Customer Data Platforms (CDP) for marketing, personalization, or customer analytics use cases on Azure. Familiarity with data privacy frameworks and compliance standards (e.g., GDPR, CCPA). Exposure to machine learning pipelines or data science workflows integrated with EDP/CDP on Azure. Knowledge of hybrid or multi-cloud environments involving Azure and other platforms.