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Data Engineer
Role & responsibilities
Designs ETL workflows, manages data models and storage, enforces quality and security, optimizes performance, and partners with analysts and engineers.
Key strengths
- Technical skills32% (Job)
- Analytical thinking20% (Job)
- Problem solving18% (Job)
- Attention to detail12% (Job)
- Communication10% (Job)
- Teamwork8% (Job)
What this means for you
- Technical skills – Designs reliable data pipelines and infrastructure.
- Teamwork – Collaborates with downstream users to keep data usable.
- Analytical thinking – Chooses models and partitions that balance cost and speed.
Typical tasks
- Optimize performance, security, and reliability of data platforms
- Design and build data pipelines and storage solutions
- Model datasets for analytics and maintain data quality
Daily work
- Partners with analysts and scientists on schema and performance
- Checks pipeline runs and data quality alerts
- Builds or refines ingestion, transformation, and storage layers
Education & entry routes
Helpful but not mandatory
- Cloud data certifications
- Data pipeline or SQL optimization courses
Alternative pathways
- Analytics Platform Administrator
- BI Developer
- ETL Developer
Work environment
- Team size
- Works within data engineering and analytics teams
- Typical employers
- Tech companies, data platforms, enterprise analytics groups
- People contact
- Collaboration with data scientists, analysts, and product teams
- Stress level
- Moderate, higher during migrations or incidents
- Working hours
- Flexible hours aligned to sprint cycles with on-call for pipelines
Entry & progression
Common entry roles
- Data Engineer Intern
- ETL Developer
Next career steps
- Data Platform Lead
- Senior Data Engineer