Lead Data Engineer

Are you ready to shape the future of supply chain and logistics at H&M through data? We are looking for two Lead Data Engineers to join our rapidly expanding Supply Chain and Enterprise area and play a pivotal role in building scalable, maintainable, and high-impact data solutions within AI & Data domain. At H&M, we are on a transformative journey to exceed customer expectations through the power of data, technology, and innovation. Our SC&E area is scaling fast, and we need experienced technical leaders who thrive in dynamic environments and are passionate about technical mentoring team and driving delivery excellence. Join us in creating a smarter, more connected supply chain that supports millions of customers across the globe. As a Lead Data Engineer in the SC&E area, you will drive technical advancements, lead complex and high-priority data projects, and foster a collaborative and innovative engineering culture. You will be instrumental in designing and delivering scalable data products aligned with our strategic vision, mentoring engineering talent, and ensuring high-quality execution across initiatives. You will work within the AI, Analytics & Data domain, collaborating closely with product management, business stakeholders, and other engineering teams to ensure our data foundation supports the evolving needs of the business. WHAT YOU’LL DO: - Lead the design and implementation of robust, scalable data architectures and ETL/ELT processes. - Provide technical oversight and guidance to multiple product teams. - Champion DevOps principles, managing CI/CD pipelines and cloud infrastructure (GCP). - Ensure data products meet standards for security, scalability, observability, and performance. - Mentor engineering talent, promoting a culture of growth, accountability and critical thinking. - Collaborate with Product managers, Solution Architects, and stakeholders to align technical execution with business goals across the program. - Drive cross-functional collaboration to ensure secure and efficient business delivery. - Use business context to guide product scope and technical decisions. - Support team members across disciplines and promote shared learning and continuous improvement. - Identify and implement emerging technologies relevant to organizational goals. - Represent the product team across organizational levels and domains from a technical perspective. - Contribute across different product teams within or across programs to define scope, prioritize tasks and resolve technical issues WHO YOU ARE: We are looking for people with… - Senior data engineer with a technical degree (BE, B.Sc or similar) in a relevant field. - 7+ years of experience in data engineering with proven leadership in complex projects. - Strong skills in data engineering (Python, Java, or Scala) and production-grade software development. - Experience in architecting and implementing scalable data solutions with Batch/Streaming data - Experience with modern cloud data platforms (preferably GCP). - Proficiency in data formats (Avro, Parquet), query languages (SQL), and data modeling techniques. - Familiarity with tools like Apache Spark, Terraform, and data processing frameworks (Beam, Spark, Hive, Flink). - Exposure to event based data modeling and familiarity with EPCIS/GS1 standards - Good understanding of H&M or equivalent industry operations. - Experience with NoSQL and RDBMS databases. - Excellent communication and collaboration skills. - Fluent in English (written and verbal). - Familiarity with Agile practices. - Proven record of contributing towards multiple products and teams within or across programs - Actively participated and contributed in different data engineering community practices within the unit Also preferred if you have: - Experience with GCP tools (Dataflow, Dataproc, BigQuery). - Experience with DBT or similar Data transformation tools. - Business understanding of the retail industry and supply chain area. - Experience in working with data visualization tools. Key Behaviours: - Collaboration: Foster teamwork and shared learning across teams. - Empowerment: Enable others to take ownership and grow. - Innovation: Drive creative solutions and embrace emerging technologies. - Continuous Improvement: Focus on refining processes and reducing technical debt. - Resourcefulness: Solve problems effectively with available tools and knowledge. - Integrity: Communicate with honesty, clarity, and transparency.