P1P1 — Entry-Level Professional
Data Engineering Entry/Mid
They focus on building pipeline components and fixing issues under guidance.
What this level means
New to role or field; performs basic tasks under supervision
- Scope
- Own tasks within a defined component
- Autonomy
- Close supervision; work reviewed frequently
- Complexity
- Routine problems with known solutions
- Impact
- Own deliverables
- Decision rights
- Few independent decisions; escalates the rest
- Leadership
- None — building the craft
- Typical experience
- 0–2 yrs
What you'd do
- Build or maintain simple data pipelines
- Write queries to extract data
- Assist in data cleaning and preparation
- Support data integration efforts
- Collaborate with data analysts to understand data needs
- Document data processes and pipelines
- Perform basic data validation and quality checks
- Monitor data pipeline performance
- Maintain pipeline uptime
- Reduce error rates
- Ensure data throughput
- Assist in developing ETL processes
- Support data warehouse maintenance
- Collaborate with data analysts to optimize data flow
- Document pipeline processes
- Perform routine data quality checks
- Build simple data pipelines.
- Write data extraction queries.
- Assist in data cleaning.
- Support data integration.
- Document processes.
- Monitor and maintain data pipelines
- Assist in ETL process development
- Conduct data quality checks
Skills, knowledge & tools
- SQL querying
- Python scripting
- Data pipeline maintenance
- Data extraction
- Data cleaning
- Data validation
- Documentation
- Performance monitoring
- Basic ETL process knowledge
- SQL proficiency
- Python or Java skills
- Data warehousing basics
- Troubleshooting
- Version control systems
- Basic cloud platform usage
- Relational databases
- Data pipeline concepts
- Basic data modeling
- Data integration techniques
- Data validation methods
- SQL optimization
- Basic scripting
- Data quality assurance
- ETL processes
- Data warehousing
- Error handling
- Data throughput optimization
- Technical documentation
- Basic cloud infrastructure
- Strong SQL
- Basic Python/Scala scripting
- Attention to detail
- Problem-solving
- Communication Skills
- Team collaboration
- Basic data modeling
- Data integration
- Pipeline uptime
- Error rate
- Data throughput
- Collaboration
- Technical documentation
- Adaptability
What good looks like
- Strong SQL
- Basic Python/Scala scripting
- Experience with relational databases
- Bachelor’s degree in Computer Science or related field
- Internship experience in data engineering
- Basic understanding of data pipelines
- Experience with ETL processes
- Bachelor's degree in Computer Science or related field
- 0-2 years of experience in data engineering
- Strong analytical skills
Common titles
Data Engineering IData Engineering 1Entry-Level Data EngineeringJunior Data EngineeringAssociate Data EngineeringData Engineer IData Engineer 1Entry-Level Data EngineerJunior Data EngineerAssociate Data EngineerData Engineering Entry/MidP1–P4
Where it sits & what it pays
O*NET / SOC: 15-0000 — Computer & Mathematical Occupations(inferred · under review)
Market-pay benchmarks for this family × level are coming — JobFrame anchors pay to the family/level structure rather than the raw title.