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Director, Software Engineering
4 months ago
As a Director of Enterprise Data, you will play a key role in managing and evolving our Azure-based data-bricks offerings and Features, developing strategic data initiatives. You will also be responsible for optimizing the data warehousing capabilities and building upon our data-driven decision-making processes. Your outstanding communication skills will be pivotal in bridging the gap between the technical and business worlds, ensuring that complex data challenges are clearly communicated and efficiently addressed. You will step into a significant role where you can drive change, promote innovation, and work in partnership with our talented data lake team. We offer a collaborative and supportive environment where you can continuously learn, grow, and lead us on our journey to become a data-driven fashion retail industry leader.What You'll Do
- Work closely with the Director of Data Warehousing to ensure the design, development, and maintenance of our Azure-based data lake (Data-Bricks SQL) meets and exceeds business needs.
- Implement efficient data processing systems using Azure Data Bricks and oversee the development of high-performance data pipelines that ensure data quality and integrity.
- Collaborate with various organizational leaders and stakeholders to deliver precise data solutions that address their unique needs.
- Guide the optimization of ETL (Extract, Transform, and Load) processes and work alongside the data warehousing team to steer our journey toward a more data-driven future.
- Foster a data-driven culture within the organization and advocate for the use of data and analytics in decision-making across all levels.
- Lead and mentor a dynamic data engineering team, promoting a culture of continuous innovation, and providing opportunities for professional development.
- Exceptional knowledge of Azure technologies, including Azure Databricks, Azure Data Factory, and Power BI, and a commitment to staying current with Azure's latest products and services.
- Proficiency in SQL, Python, and other data manipulation languages.
- Deep understanding of data architecture, data modeling, and performance tuning.
