
Data Systems Developer
3 days ago
We are a forward-thinking fashion brand dedicated to creating high-quality, innovative products that drive business success. At Happy Socks, we leverage technology to gain valuable insights and improve operational efficiency. Our data team plays a critical role in shaping our data-driven culture and empowering informed decision-making across the organization.
Role Overview:
- As a skilled Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support various data initiatives.
- You will work closely with analytics specialists, analysts, and other engineers to ensure clean, reliable, and well-structured data is available for business decision-making.
- Contribute to the planning, design, and architecture of the data foundations project, resulting in a comprehensive roadmap for our Data Platform.
Key Responsibilities:
- Design, build, and maintain scalable data pipelines to support ELT/ETL processes and data warehousing as well as pulling data from various data sources.
- Collaborate with analytics specialists, analysts, and other teams to ensure data availability, correctness, and reliability.
- Maintain and ensure the proper functioning of our Data Warehouse, which is at the heart of the data platform.
- Set up data modeling and transformation frameworks in line with business processes, resulting in aggregated or transformed views or tables ready for downstream consumption.
- Serve data that is ready for consumption in downstream applications like reports or dashboards as required by business users.
Requirements:
- Strong operational skills with the ability to ensure pipelines and systems are running smoothly, including proactive monitoring and issue identification.
- Strong attention to detail and ability to ensure data correctness and consistency.
- Proven experience in data modeling, data warehousing, designing and building data pipelines and ELT/ETL processes.
- Strong proficiency in SQL and experience with at least one programming language (e.g., Python).
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