P1
DENG.GEN.P1
Data Engineering Entry/Mid
Data Engineering
Data Engineering Entry/Mid
DENG.GEN.P1
P1P1 — Entry-Level Professionalmedium0.70draftglobalv1
They focus on building pipeline components and fixing issues under guidance.
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Level
P1 · P1 — Entry-Level Professional · 0–2 yrs
Function · Focus
Data Engineering · General
Market pay (median)
—
Pay basis
model pending
They focus on building pipeline components and fixing issues under guidance.
The story of this role
Who does this work
A Data Engineer who wants to master the art of building efficient data pipelines and infrastructure to empower organizations with actionable insights.
The problem this role solves
- The external problem: Organizations struggle with unorganized data and lack proper infrastructure to harness it for decision-making.
- The internal problem: The Data Engineer feels overwhelmed by the complexity of data systems and the pressure to deliver insights quickly.
- Why it matters: Every organization deserves to have seamless access to its data to drive innovation and growth.
The plan
- Develop expertise in critical thinking to analyze complex data requirements.
- Enhance reading comprehension to stay updated with the latest technologies and methodologies in data engineering.
- Utilize active listening skills to understand stakeholder requirements and challenges in data management.
- Apply complex problem-solving skills to design and implement robust data architectures.
- Leverage knowledge in geography, biology, and electronics to build specialized data solutions tailored to different industries.
What's at stake
Inadequate data infrastructure leads to missed opportunities and poor decision-making in the organization. The Data Engineer feels stagnant in their career due to a lack of effective skills and misalignment with organizational needs.
Success looks like
The organization efficiently accesses and utilizes its data, leading to informed decision-making and strategic growth. The Data Engineer becomes a trusted expert in their field, driving data strategy and innovation within the organization.
Summary
They focus on building pipeline components and fixing issues under guidance.
Level — P1 — Entry-Level Professional
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
Core outputs
No core outputs recorded yet.
Adjacent roles
Nearest roles by structural coordinates (level + taxonomy). Distance 0 → 1; each carries its 3-state match band. How coordinates work → · Compare side-by-side →
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Componentsshow ▾
Responsibilities16
- Build or maintain simple data pipelinescommonlevel
- Write queries to extract datacommonlevel
- Assist in data cleaning and preparationcommonlevel
- Support data integration effortscommonlevel
- Collaborate with data analysts to understand data needscommonlevel
- Document data processes and pipelinescommonlevel
- Perform basic data validation and quality checkscommonlevel
- Monitor data pipeline performancecommonlevel
- Maintain pipeline uptimecommonlevel
- Reduce error ratescommonlevel
- Ensure data throughputcommonlevel
- Assist in developing ETL processescommonlevel
- Support data warehouse maintenancecommonlevel
- Collaborate with data analysts to optimize data flowcommonlevel
- Document pipeline processescommonlevel
- Perform routine data quality checkscommonlevel
Tasks8
- Build simple data pipelines.commonlevel
- Write data extraction queries.commonlevel
- Assist in data cleaning.commonlevel
- Support data integration.commonlevel
- Document processes.commonlevel
- Monitor and maintain data pipelinescommonlevel
- Assist in ETL process developmentcommonlevel
- Conduct data quality checkscommonlevel
Skills15
- SQL queryingcommonlevel
- Python scriptingcommonlevel
- Data pipeline maintenancecommonlevel
- Data extractioncommonlevel
- Data cleaningcommonlevel
- Data validationcommonlevel
- Documentationcommonlevel
- Performance monitoringcommonlevel
- Basic ETL process knowledgecommonlevel
- SQL proficiencycommonlevel
- Python or Java skillscommonlevel
- Data warehousing basicscommonlevel
- Troubleshootingcommonlevel
- Version control systemscommonlevel
- Basic cloud platform usagecommonlevel
Knowledge14
- Relational databasescommonlevel
- Data pipeline conceptscommonlevel
- Basic data modelingcommonlevel
- Data integration techniquescommonlevel
- Data validation methodscommonlevel
- SQL optimizationcommonlevel
- Basic scriptingcommonlevel
- Data quality assurancecommonlevel
- ETL processescommonlevel
- Data warehousingcommonlevel
- Error handlingcommonlevel
- Data throughput optimizationcommonlevel
- Technical documentationcommonlevel
- Basic cloud infrastructurecommonlevel
competency14
- Strong SQLcommonlevel
- Basic Python/Scala scriptingcommonlevel
- Attention to detailcommonlevel
- Problem-solvingcommonlevel
- Communication Skillscommonlevel
- Team collaborationcommonlevel
- Basic data modelingcommonlevel
- Data integrationcommonlevel
- Pipeline uptimecommonlevel
- Error ratecommonlevel
- Data throughputcommonlevel
- Collaborationcommonlevel
- Technical documentationcommonlevel
- Adaptabilitycommonlevel
qualification10
- Strong SQLcommonlevel
- Basic Python/Scala scriptingcommonlevel
- Experience with relational databasescommonlevel
- Bachelor’s degree in Computer Science or related fieldcommonlevel
- Internship experience in data engineeringcommonlevel
- Basic understanding of data pipelinescommonlevel
- Experience with ETL processescommonlevel
- Bachelor's degree in Computer Science or related fieldcommonlevel
- 0-2 years of experience in data engineeringcommonlevel
- Strong analytical skillscommonlevel
Title aliasesshow ▾
| Alias | Type | Confidence | Approved |
|---|---|---|---|
| Data Engineering I | common | medium0.70 | — |
| Data Engineering 1 | common | medium0.66 | — |
| Entry-Level Data Engineering | common | medium0.70 | — |
| Junior Data Engineering | common | medium0.68 | — |
| Associate Data Engineering | common | medium0.60 | — |
| Data Engineer I | common | medium0.70 | — |
| Data Engineer 1 | common | medium0.66 | — |
| Entry-Level Data Engineer | common | medium0.70 | — |
| Junior Data Engineer | common | medium0.68 | — |
| Associate Data Engineer | common | medium0.60 | — |
| Data Engineering Entry/Mid | common | medium0.60 | — |
| P1–P4 | common | medium0.50 | — |
Classification mappingsshow ▾
O*NET / SOC
- code=15-0000title=Computer & Mathematical Occupationssource=inferred_from_superfunctionreviewStatus=needs_review