Senior Data Engineer Azure

Job Details

We’re the world’s leading data, insights, and consulting company; we shape the brands of tomorrow by better understanding people everywhere.

About The Job

In this hands-on role, the Senior Data Engineer will be pivotal in ensuring the reliability, accuracy, and performance of our data pipelines! Our brand guidance systems are used by a global customer base to derive actionable insights for growth, making data quality essential. You will spearhead the design and implementation of resilient data pipelines.

As part of a passionate cross-functional team, you will collaborate closely to maintain the quality of our production services. Your contributions will have a significant impact on delivering reliable insights that drive brand growth globally! In this role, you will also be responsible for ensuring the seamless integration of data processes within the wider team dynamics.

Job Goals

• Design and implement resilient data pipelines to ensure data reliability, accuracy, and performance.
• Collaborate with cross-functional teams to maintain the quality of production services and smoothly integrate data processes.
• Oversee the implementation of common data models and data transformation pipelines, ensuring alignement to standards.
• Drive continuous improvement in internal data frameworks and support the hiring process for new Data Engineers.
• Regularly engage with collaborators to discuss considerations and manage the impact of changes.
• Support architects in shaping the future of the data platform and help land new capabilities into business-as-usual operations.
• Identify relevant emerging trends and build compelling cases for adoption, such as tool selection.
  
  

• A minimum of three years of experience in a comparable Senior Data Engineer position is required.
• Data Engineering Expertise: Proficiency in designing and implementing resilient data pipelines, ensuring data reliability, accuracy, and performance, with practical knowledge of modern cloud data technology stacks (Azure Only).
• Technical Proficiency: Experience with Azure Data Factory and Databricks, and skilled in Python, Apache Spark, or other distributed data programming frameworks.
• Operational Knowledge: In-depth understanding of data concepts, data structures, modelling techniques, and provisioning data to support varying consumption needs, along with accomplished ETL/ELT engineering skills.
• Automation & DevOps: Experience using DevOps toolchains for managing CI/CD and an automation-first mindset in building solutions, including self-healing and fault-tolerant methods.
• Data Management Principles: Practical application of data management principles such as security and data privacy, with experience handling sensitive data through techniques like anonymisation/tokenisation/pseudo-anonymisation.