Builds the pipelines and data platforms that analytics and AI depend on.
Entry
Intermediate
Coding
High
Key skills
Career overview
The Data Engineer makes data usable: ingestion from dozens of sources, transformation, modelling, orchestration, quality checks, cost and performance. Without this plumbing, dashboards lie and machine learning models starve. The role combines software engineering, SQL mastery and platform thinking.
Main responsibilities
- Build reliable data ingestion pipelines
- Model and maintain the data warehouse
- Guarantee data quality, freshness and lineage
- Write, test and review production code
- Describe infrastructure as code and version it
- Monitor platform health, alerts and dashboards
- Track and optimise cloud spending
- Keep technical documentation up to date
- Model and query relational databases
- Write unit and integration tests
Technical skills
Technologies
Education level
Education requirements vary depending on the company, country and experience. Professional experience, certifications and technical skills can sometimes compensate for formal education.
High School / Bac
Less common
Bac+2 (2-year degree)
Less common
Bac+3 (Bachelor)
Common entry point
Bac+5 (Master / Engineering)
Common entry point
Experience & coding level
Experience level
Coding level
Useful certifications
Certifications are never mandatory. They are one way among others to prove a skill.
- Google Professional Data Engineer
- AWS Data Analytics Specialty
- dbt Analytics Engineering
Where can this career take you?
Multiple paths are possible. Click a role to open its profile.
Direct progression
Possible branches
Where can you go next?
Realistic next career moves, with compatibility and a transition roadmap for each.
Overlap: 20% · Difficulty: Hard
Skills to learn: Observability & tracing, Kubernetes, Linux internals
View roadmapOverlap: 23% · Difficulty: Medium
Skills to learn: AWS / Azure / GCP, Terraform, Identity & access management
View roadmapOverlap: 25% · Difficulty: Hard
Skills to learn: Kubernetes, Terraform & IaC modules, CI/CD at scale
View roadmapOverlap: 12% · Difficulty: Medium
Skills to learn: AWS / Azure / GCP, Terraform, Landing zones
View roadmapWhere can you go from here?
A typical progression built from real career relationships. Click any role to open its profile.
Soft skills
- Rigour and attention to detail
- Problem solving
- Technical curiosity
- Clear communication
- Big-picture thinking
- Documentation writing
Common previous careers
Roles that frequently lead into this career.
Overlap: 15% · Difficulty: Hard
Skills to learn: Python, Orchestration (Airflow), Data modelling
View roadmapOverlap: 24% · Difficulty: Hard
Skills to learn: SQL, Python, Orchestration (Airflow)
View roadmapOverlap: 50% · Difficulty: Medium
Skills to learn: SQL, Orchestration (Airflow), Spark / distributed processing
View roadmapOverlap: 24% · Difficulty: Medium
Skills to learn: SQL, Orchestration (Airflow), Data modelling
View roadmapRelated resources
Continue your career exploration
Keep moving: compare roles, follow a roadmap, read a guide or prepare for an interview.
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A documented transition from this role to the next.
Data EngineerSite Reliability Engineer
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