Senior Data Engineer at Digital Zone
Indexed description
In our short lifetime since Digital Zone was founded, we achieved growth and success metrics that are unforeseen in the region, where “stretch for amazing” became our daily business. Our success is outgrowing our capacity, and now is the time to grow our team.
Our Data Team brings together experienced Data Analysts and Data Engineers with strong backgrounds in data pipelines, analytics, statistics, and experimentation. We work closely with cross-functional teams across Finance, Operations, Product, Growth, and Marketing, providing data that drives everyday decisions and long-term growth.
What You’ll Be Doing
- Design, build, and own end-to-end data pipelines across multiple systems (Raw - Curated - Warehouse)
- Develop and maintain scalable, reliable ETL/ELT workflows using Python.
- Lead data modeling and optimization efforts in both, traditional transactional databases and analytical data warehouses for reporting & analytics.
- Anticipate and manage the downstream impact of data engineering decisions across analytics, BI, and product use cases
- Proactively identify, debug, and resolve data quality, performance, and reliability issues
- Optimize pipeline performance, cost, and scalability across storage, compute, and orchestration layers
- Establish and enforce best practices for data engineering, documentation, version control, code reviews, and deployment using Github.
- Build reusable, maintainable, and auditable pipelines with clear assumptions and traceability
- Partner closely with Data Analysts, Product, Operations, Finance, and Tech teams to translate business needs into robust data solutions
- Contribute to the evolution of the modern data stack, evaluating trade-offs and introducing improvements where appropriate
- Promote a strong data culture through mentorship, technical leadership, and clear communication
- 4–6+ years of experience as a Data Engineer or in a similar data-focused engineering role
- Strong experience building production-grade data pipelines using Python
- Strong proficiency in SQL and deep hands-on experience with PostgreSQL and ClickHouse is a plus
- Hands-on experience with orchestration tools like Airflow, Dagster, or Mage and data ingestion tools like Airbyte
- Experience working with data lakes, like AWS S3, Azure Blob storage, or Google Cloud Storage
- Solid understanding of ETL/ELT design patterns, data modeling fundamentals, and analytical warehouses
- Strong version control and collaboration skills using GitHub
- Proven ability to design and maintain reliable, scalable, and reusable systems
- Experience ensuring data quality, consistency, lineage, and documentation
- Ability to evaluate architectural trade-offs and make sound engineering decisions
- Comfortable working across multiple projects with interdependencies
- Experience supporting analytics and BI use cases (Metabase or similar tools)
- Prior experience in e-commerce or marketplace data is a plus
- Advanced English communication skills is a plus
- High ownership and accountability for end-to-end systems and outcomes
- Proactive communication with technical and non-technical stakeholders
- Ability to lead technical discussions and set expectations
- Strong documentation and knowledge-management discipline
- A mindset that balances technical excellence with business impact
- Openness to feedback and a culture of continuous improvement
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