Teya
Senior Data Engineer
Remote Senior Data Engineer role with clear candidate location fit.
PostedJun 11, 2026
Eligible countries37 accepted countries
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Role overview
Senior Data Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Your main responsibilities will include:
- Designing and evolving the architecture of our data warehouse and data platform
- Transforming complex data models into scalable, production-ready data products
- Building, maintaining, and improving data models for large and complex datasets
- Designing and optimising ETL/ELT pipelines to support scalable analytics and data products
- Establishing reliable, well-governed datasets that serve as a foundation for analytics and AI/ML use cases
- Improving data reliability, quality, and observability across key datasets
- Collaborating with stakeholders to define and deliver high-impact data products
- Driving automation and improvements across a legacy ETL ecosystem (~1500 pipelines)
- Contributing to engineering standards, documentation, and best practices within the data engineering team
- Staying informed about modern data platform technologies and industry best practices, contributing ideas that help evolve our data stack and engineering practices.
Your Story
- Strong SQL expertise, particularly in complex analytical and warehouse queries
- 5+ years experience in Data Engineering, Analytics Engineering, or Data Platform Engineering
- Strong experience with data warehousing, dimensional modelling, and data architecture
- Experience designing and delivering scalable data products
- Experience with ETL/ELT tooling (DBT, SSIS, Wherescape, or similar)
- Strong understanding of data pipeline architecture and distributed data systems
- Proficiency in Python or a similar programming language
- Understanding of how data platforms support machine learning and AI workflows
- Strong grasp of software engineering principles and best practices
- Experience contributing to or leading data warehouse architecture or redesign initiatives
- Ability to collaborate effectively with technical and non-technical stakeholders
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Location eligibility
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Hiring flow
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