Data Engineer

**Job description**:
** About Sellerwix**

Sellerwix is a fast-growing Print-on-Demand (POD) technology company. We power fulfillment, integrations, and automation for high-volume POD sellers across global marketplaces. We’re on a mission to build a technology-first platform that enables sellers to scale smarter and faster.

** Position Summary**

As a **Data Engineer** at Sellerwix, you’ll play a key role in building and scaling the **data backbone** that powers our platform.

You will design and manage high-performance data pipelines, integrate data from multiple POD and marketplace sources, and ensure our business teams have accurate, real-time insights to make fast, data-driven decisions.

** Job Description**
- Design, build, and maintain automated data pipelines that extract and process data from marketplaces (Amazon, Etsy, TikTok Shop, etc.) and POD suppliers. Architect and optimize data warehouses (Redshift / BigQuery / Snowflake) to manage high-volume eCommerce data flows from listing order production shipping
- claims.
- Develop data models, marts, and transformations to support business domains like Revenue, Fulfillment, and Supplier Performance.
- Implement data quality checks, validation logic, and alert systems to ensure reliability and trustworthiness of insights.
- Build and maintain real-time data integrations with Sellerwix internal systems and external APIs.
- Collaborate with Data Analysts, Sales, Supply Chain, and Operations teams to define metrics and deliver BI dashboards (Power BI / Tableau / Looker / Superset).
- Continuously improve system scalability, automation, and data observability.

**Your skills and experience**:
** Requirements**

** Must-Have**:

- Solid proficiency in **SQL** and **Python** (Pandas, NumPy, SQLAlchemy).
- Proven experience with **ETL/ELT workflows** (Airflow, AWS Glue, or GCP Dataflow).
- Hands-on experience managing **data warehouses** (Redshift / BigQuery / Snowflake).
- Familiarity with **RESTful APIs** and real-time data synchronization.
- Strong understanding of **data modeling** and **performance optimization**.
- 2+ years of experience as a Data Engineer, preferably in **eCommerce, SaaS, or POD** domains.
- Experience building dashboards or data models using **Power BI / Tableau / Looker** / **Superset.**

** Nice-to-Have**:

- Understanding of the **Print-on-Demand lifecycle** (listing production shipping claim/refund).
- Experience with **marketplace data structures** (Amazon SP-API, TikTok Shop API, Etsy API).
- Familiarity with **dbt**, **Kafka**, or **Fivetran** for modern data stack orchestration.
- Experience implementing **data observability or anomaly detection systems**.
- Interest in **ML data preparation or predictive analytics**.

** Who We Look For**
- Analytical and detail-oriented with a strong drive for **data accuracy and automation**.
- Proactive in identifying inefficiencies and suggesting process or pipeline improvements.
- Able to communicate clearly across technical and business teams.
- Thrive in a **fast-paced, startup-like environment** with evolving priorities.
- Constant learner who keeps up with modern data tools and architecture trends.

**Why you'll love working here**:
** Why you’d love to work with us**
- Opportunity to **build the data core** of one of Asia’s fastest-growing POD tech platforms.
- Work with **real-world, large-scale eCommerce data** powering automation and insights for global sellers.
- Modern toolset: Airflow, BigQuery, dbt, Power BI, Grafana, etc.
- **Competitive salary & bonuses** with 13th-month pay and quarterly performance incentives.
- **12 annual leave days + 5 sick leave days.**
- **Insurance contributions are based on 90% of the gross salary.**
- **PTI insurance is effective** from day one of your labor contract.
- Cash bonuses on holidays, birthdays, and company events.
- Friendly, non-hierarchical culture with open communication and high ownership.
- Dedicated training roadmap and a **clear career growth path**.
- Weekly Happy Hours, annual company trips, and plenty of free drinks.

** The recruitment process would be short and sweet**
- Up to **2 rounds of interviews** (Technical + Culture Fit).
- Quick offer decision and onboarding.