Data Engineer

at  Huda Beauty

Who We Are: At Huda Beauty, our Vision is to lead in creating a democratized beauty industry where power is given back to people to define, create, and enjoy beauty for themselves! Launched by award-winning beauty powerhouse Huda Kattan in 2013, Huda Beauty is one of the world’s fastest growing beauty brands. As a company, we are fueled by purpose which allows us to approach things differently so that we can create products, content, and a community like no other. A lot has changed since our launch in 2013, but something that will forever remain at the core of Huda Beauty is our focus on business excellence and our unwavering passion for kindness!
Summary: The Data Engineer will be pivotal in architecting and executing the data strategy within our cloud-based infrastructure, aiming to empower business intelligence and data-driven decision-making across the organization. In this capacity, the specialist will drive the development of robust ETL/ELT pipelines for diverse data integration, manage scalable solutions within Azure Synapse Analytics, and oversee the maintenance of extensive database systems.
By producing insightful data visualizations and optimizing data models, they will directly contribute to enhancing business operations and analytics capabilities. With adept skills in Python and SQL, this role will further automation and scripting to streamline data workflows. Acting as a key interface, the specialist will collaborate with data scientists and various business units to translate complex data needs into tangible solutions. Reporting to the Head of Data Management, this role requires a strong foundation in cloud computing, data warehousing, and analytical problem-solving, and will involve leadership over external data service providers.

REQUIREMENTS

Essential Duties and Responsibilities:

• Data Pipeline Development: Design and implement robust ETL/ELT pipelines using Azure Data Factory and/or Azure Synapse Pipelines to ingest data from various structured and unstructured sources.
• Azure Synapse Expertise: Build and manage scalable data warehouses and data lakes within Azure Synapse Analytics, ensuring optimal performance and data governance.
• Large-Scale Database Management: Design and maintain large-scale relational and/or NoSQL databases in Azure (e.g., Azure SQL Database, Azure Cosmos DB) to support business applications and analytical queries.
• Data Visualization and Reporting: Develop compelling data visualizations and dashboards in Power BI, delivering valuable insights to stakeholders at all levels.
• Data Modeling and Optimization: Optimize data models for efficient storage and retrieval, and performance-tune data processing workloads.
• Coding and Scripting: Utilize Python and SQL extensively for data querying, transformation, and analysis, and contribute to automating data-related tasks.
• Collaboration: Work closely with data scientists, analysts, and business teams to understand data needs and translate them into effective data solutions.

REQUIREMENTS

• Education: Bachelor’s degree in computer science, data science, or a related field.
• Cloud Proficiency: Proven experience in architecting and implementing data solutions on the Microsoft Azure platform.
• Azure Synapse: Strong working knowledge of Azure Synapse Analytics (data warehousing, data lakes and pipelines).
• Database Technologies: Experience with a variety of Azure database technologies (Azure SQL Database, Azure Cosmos DB, etc.), along with traditional SQL skills.
• Power BI: Proficiency in creating interactive dashboards and reports in Power BI.
• Programming Languages: Excellent Python skills for data manipulation, scripting, and automation.
• Problem-Solving: Strong analytical and troubleshooting skills.
• Communication: Excellent written and verbal communication skills to collaborate effectively with technical and non-technical stakeholders.
• Desired Experience (Nice to Have)
• Familiarity with big data technologies (e.g., Apache Spark, Hadoop).
• Experience with stream processing tools (e.g., Azure Stream Analytics, Kafka).
• Knowledge of DevOps and CI/CD practices.
• Relevant Azure certifications (e.g., Azure Data Engineer Associate)

• Data Pipeline Development: Design and implement robust ETL/ELT pipelines using Azure Data Factory and/or Azure Synapse Pipelines to ingest data from various structured and unstructured sources.
• Azure Synapse Expertise: Build and manage scalable data warehouses and data lakes within Azure Synapse Analytics, ensuring optimal performance and data governance.
• Large-Scale Database Management: Design and maintain large-scale relational and/or NoSQL databases in Azure (e.g., Azure SQL Database, Azure Cosmos DB) to support business applications and analytical queries.
• Data Visualization and Reporting: Develop compelling data visualizations and dashboards in Power BI, delivering valuable insights to stakeholders at all levels.
• Data Modeling and Optimization: Optimize data models for efficient storage and retrieval, and performance-tune data processing workloads.
• Coding and Scripting: Utilize Python and SQL extensively for data querying, transformation, and analysis, and contribute to automating data-related tasks.
• Collaboration: Work closely with data scientists, analysts, and business teams to understand data needs and translate them into effective data solutions