Area Manager - Data Engineering & AI Automation

Imagine an opportunity to make an impact at scale by leading the strategy, design, development, and implementation through managing your own Data Engineering team within HM Tech Organization!

As a leader, you will develop Data Engineering strategies overseeing the design, construction, installation, and maintenance of data architecture, ensuring the seamless flow and accessibility of data across the organization to maximize HM Brand s business value.

You thrive in fostering teamwork/collaboration and developing world-class Strategic, Technical, Engineering, and Operational capabilities. We are shaping the future of sustainable fashion and design- we trust and challenge you to grow, develop, and write your own story!

Core Responsibilities includes but is not limited to:

Leadership:

1. Drive and lead the design a multi-year data and product strategy to create new data products and drive measurable competitive advantage for HM. Determine the investments necessary in terms of people and technology to achieve these objectives
2. Explore data engineering, data science and AI developments and translate these to the data strategy to keep HM on the cutting edge of data optimization.
3. Provide strategic leadership and vision for the data engineering team.
4. Promote identification of new internal and external data assets; approve selection and integration
5. Build and lead a high-performing team, fostering a culture of innovation, collaboration, and continuous improvement.
6. Collaborate with cross-functional teams, including data science, analytics, and IT, to align data engineering initiatives with overall business objectives.
7. Formal staff responsibility, including salary review, performance dialogues and support in individual development plans and competence needs

Data Architecture:

1. Develop and implement a scalable and robust data architecture to support current and future business needs.
2. Define and enforce data engineering standards, best practices, and guidelines.
3. Stay abreast of industry trends and emerging technologies to ensure the organization remains at the forefront of data engineering capabilities.

Data Integration and ETL:

1. Oversee the development and maintenance of efficient and scalable ETL processes for data integration.
2. Ensure the timely and accurate extraction, transformation, and loading of data from various sources into the data warehouse.
3. Data Quality and Governance:
4. Implement data quality and governance processes to ensure the accuracy, completeness, and reliability of the organizations data.
5. Establish and enforce data security and privacy measures in compliance with regulatory requirements.

Infrastructure Management:

1. Manage and optimize data infrastructure, including databases, storage, and processing systems.
2. Collaborate with IT teams to ensure the availability, performance, and scalability of data systems.