Senior Data Engineer, Global E-Commerce Data Platform (Total Annual Income $40,000)

Join our Technology Innovations Center of Excellence (CoE) at Crossian, a fast-growing startup that achieved a milestone of $100M in 2024. In this dynamic role, you'll check in daily with your team to stay aligned on project goals and collaborate across our ecosystem with an Agile mindset infused with a unicorn-worthy startup culture.
We are building an E-commerce Data Platform following Lakehouse Architecture, leveraging Airflow, Airbyte, dbt, and Redshift on AWS Cloud. Our system is currently in the early development stage, providing a unique opportunity for you to be involved from the ground up-shaping the architecture, defining data pipelines, and implementing best practices. Here are some examples: Storefront, Payment Gateway, Inventory, Catalog, Logistics, Marketing Insights, CRM.
Why join us?
We're not just about building platforms; we're about creating a workplace where talent thrives. Here's what you'll gain:
Exceptional Compensation
• Up to 30 months of salary per year through competitive salary packages and performance-based bonuses.
• Total annual income $30,000, reflecting your expertise and contribution.
Growth Opportunities
• Hands-on exposure to cutting-edge technologies and complex system architecture in a global-scale project.
• Clear career advancement pathways and access to continuous professional development programs.
Global Vision
• Contribute to projects that redefine how brands connect with consumers globally.
• Opportunity to work on challenging problems in data analytics, customer engagement, and operational efficiency.
In addition to development tasks, you'll collaborate closely with other CoEs to understand their unique challenges. With your technical expertise, you'll continuously propose innovative solutions to elevate their performance and contribute to the overall success of the organization.
Responsibilities
1. Collaborate with Data Analysts and Business Teams to understand data needs and provide timely solutions for reporting and insights.
2. Work on data integration from various sources, including APIs, web services, and databases.
3. Utilize tools such as AWS QuickSight, Grafana, and Google Sheets for data visualization to support business decision-making.
4. Support developing and maintaining scalable data pipelines and ETL/ELT processes to collect, clean, and process large-scale datasets in data systems.
5. Monitor data pipeline performance and troubleshoot issues to ensure data integrity and availability.
6. Document technical processes, contribute to data catalogs, and ensure compliance with data governance policies.
7. Engage in continuous learning and improvement, staying updated with industry best practices in Data Engineering.