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Data Warehouse Developer

2 months ago

London Area, United Kingdom Mentmore Full time

Data Warehouse Developer // Up to £80k plus package // Global advertising business // Hybrid Working Model (London) // Microsoft Stack


Client Summary

My client is a global marketing and communications agency that focuses on integrating creative, media, and technology to deliver innovative solutions for its clients. Known for its collaborative approach, the agency operates with a unique model that brings together multiple disciplines under one roof, ensuring seamless coordination across creative, media, data, and digital services. The business works with some of the world’s leading brands, delivering tailored campaigns that drive growth and brand recognition. Its emphasis on creativity combined with data-driven strategies and agile ways of working enables the agency to deliver impactful results in a rapidly evolving media landscape.


The Role

We are seeking a highly skilled and motivated Data Warehouse Developer to join their dynamic team. In this role, you will be responsible for designing and developing a robust data warehouse using the Microsoft Azure tech stack. You will create a scalable and high-performance architecture capable of handling very large volumes of data, ensuring data quality, consistency, and efficiency on an ongoing basis. Reporting directly to the Data Warehouse Architect, you will work closely with the Reporting and Data Science teams to understand their data requirements and manage complex data integrations from various sources. Additionally, you will support the Data Science team in gathering insights from the data using Azure's AI services.


Key Responsibilities

  • Design and develop a comprehensive data lake + data warehouse using Microsoft Azure technologies, including Azure SQL Data Warehouse, Data Factory, and Data Lake, as well as Databricks solutions.
  • Architect a scalable and performant data warehouse infrastructure to handle large volumes of data efficiently.
  • Ensure the quality, consistency, and reliability of data within the warehouse, implementing best practices for data governance and management.
  • Collaborate with the Reporting and Data Science teams to gather and understand data requirements, translating them into effective data warehouse solutions.
  • Manage and integrate complex data from disparate sources, ensuring seamless data flow and integrity.
  • Perform regular maintenance, monitoring, and optimization of the data warehouse to ensure optimal performance and efficiency.
  • Troubleshoot and resolve any issues related to data integrity, data flow, or performance within the data warehouse.
  • Support the Data Science team in leveraging Azure AI services to extract insights and actionable intelligence from the data.
  • Stay updated with the latest trends and advancements in data warehousing and Microsoft Azure technologies, providing recommendations for improvements and innovations.


Skills & Experience

  • Bachelor's degree in Computer Science, Information Technology, or a related field
  • Proven experience in designing, developing, and maintaining data warehouses using the Microsoft Azure tech stack.
  • Strong proficiency with Azure SQL Data Warehouse, Azure Data Factory, Azure Data Lake, and other relevant Azure services.
  • Deep understanding of data warehousing concepts, ETL processes, and data integration techniques.
  • Experience with handling large-scale data and ensuring data quality, consistency, and performance.
  • Proficient in SQL and other data manipulation languages.
  • Familiarity with data governance best practices and data management principles.
  • Excellent problem-solving skills and the ability to troubleshoot complex data issues.
  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
  • Detail-oriented with a focus on delivering high-quality, accurate, and efficient data solutions.
  • Experience with Azure AI services and a solid understanding of how to apply AI and machine learning techniques to gather insights from data.