Arbetsbeskrivning
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:
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Collaboration:
Foster teamwork and shared learning across teams.
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Empowerment:
Enable others to take ownership and grow.
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Innovation:
Drive creative solutions and embrace emerging technologies.
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Continuous Improvement:
Focus on refining processes and reducing technical debt.
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Resourcefulness:
Solve problems effectively with available tools and knowledge.
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Integrity:
Communicate with honesty, clarity, and transparency.