Data Warehouse Manager - Fabric Lakehouse, Pyspark

Overview

Data Warehouse Development Manager

Duration: 9 months

£580 Per Day - Inside IR35

Location:

2-3 days per month in the West Midlands, the rest can be remote working

The Data Warehouse Development Manager will lead the design, development, and implementation of an enterprise-wide data warehouse using Microsoft Fabric, consolidating data from multiple ERP systems and applications across our client's acquired businesses.

This role requires a blend of technical expertise, leadership capability, and strategic thinking to deliver a solution that meets our global client's complex reporting and analytics needs.

Our client is looking for experience of working on a Fabric Lakehouse project - someone who has completed a Lakehouse with PySpark project rather than part way through.

TXP takes great pride in representing socially responsible clients who not only prioritise diversity and inclusion but also actively combat social inequality. Together, we have the power to make a profound impact on fostering a more equitable and inclusive society. By working with us, you become part of a movement dedicated to promoting a diverse and inclusive workforce

• Lead the design, development, and implementation of an enterprise-wide data warehouse using Microsoft Fabric.
• Consolidate data from multiple ERP systems and applications across acquired businesses.
• Provide technical leadership, drive architecture decisions, and ensure solutions meet reporting and analytics needs.
• Collaborate with stakeholders to define requirements and prioritize deliverables.
• Ensure timely delivery, quality, and alignment with strategic goals.

• Strong technical and development management skills.
• Strong experience in designing and building enterprise data warehouses or data platforms in a leadership role.
• Completed a Lakehouse with PySpark project.
• Hands-on expertise in the development of a data Lakehouse within the Microsoft Fabric or Databricks data platforms.
• Significant experience with PySpark and Spark-based data processing.
• Deep understanding of data warehouse design principles, Lakehouse architectures.

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