Data Engineer

Edikted is a fast-growing global fashion brand built for the next generation of shoppers. Behind the scenes, our data team is doing something genuinely different: we're building an AI-native data platform that replaces traditional BI tools with intelligent, code-driven, self-serve systems. Instead of static dashboards and manual report-building, we're creating infrastructure where natural-language access to data, AI-assisted pipeline development, and automated validation are the default. If you're excited about working at the frontier of how AI is reshaping data engineering and want your work to directly shape how a global brand makes decisions you'll feel at home here.

About the Role

We're looking for a Data Engineer to help design, build, and maintain the pipelines and infrastructure behind our AI-powered data platform. You'll work closely with analysts, managers and cross-functional stakeholders, but you'll also be working hand-in-hand with AI tooling as a core part of your daily workflow, from generating and reviewing pipeline code to building intelligent, context-aware data systems. This is a hands-on role with real ownership and a front-row seat to what data engineering looks like in an AI-first world.

What You'll Do

• Build and maintain scalable ETL\ELT pipelines, increasingly AI-assisted, from a variety of sources (Shopify, Api's\Gql and third-party platforms)
• Develop and optimize data models that power both analytics and our natural-language, AI-driven data access layer
• Help build and extend an in-house, AI-powered platform that lets stakeholders query and explore data using Claude.
• Own orchestration, scheduling, and the reliability of production workflows, monitoring and validation
• Implement observability to keep pipelines healthy and trustworthy
• Partner with analysts and stakeholders to translate business needs into robust, intelligent data solutions
• Push forward engineering best practices (CI/CD, testing, code review) in a workflow where AI is a first-class collaborator

Requirements

• 3+ years of hands-on experience as a Data Engineer
• Strong SQL skills
• Experience working in cloud environments (e.g., AWS, Azure, or Google Cloud)
• Experience building and maintaining data pipelines and ETL/ELT processes
• Familiarity with workflow orchestration tools (e.g., Airflow, jenkins)
• Understanding of data modeling and warehouse design principles
• Curiosity and enthusiasm for working with AI tools and a desire to push how far they can go in a real production environment
• Accountability & Proactive approach

Nice to Have

• Advanced Python skills
• Strong focus on data quality
• Data modeling background — designing schemas, marts, and analytical models
• Experience with dbt and modern data-stack tooling
• Familiarity with containerization (Docker)
• Experience with monitoring/observability tools (e.g., Grafana, CloudWatch)
• Exposure to e-commerce / retail data

What We Offer

• A rare chance to build a truly AI-native data platform from the ground up not just experiment with AI on the side
• Work where AI is embedded in your everyday workflow, not an afterthought
• Real ownership and impact on company-wide decisions
• A collaborative, fast-paced team that values clean engineering and an always forward-moving approach