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Data Engineering Entry/Mid

DENG.GEN.P1

P1P1 — Entry-Level Professionalmedium0.70draftglobalv1

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

  1. Develop expertise in critical thinking to analyze complex data requirements.
  2. Enhance reading comprehension to stay updated with the latest technologies and methodologies in data engineering.
  3. Utilize active listening skills to understand stakeholder requirements and challenges in data management.
  4. Apply complex problem-solving skills to design and implement robust data architectures.
  5. 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 →

Components

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 aliases

AliasTypeConfidenceApproved
Data Engineering Icommonmedium0.70
Data Engineering 1commonmedium0.66
Entry-Level Data Engineeringcommonmedium0.70
Junior Data Engineeringcommonmedium0.68
Associate Data Engineeringcommonmedium0.60
Data Engineer Icommonmedium0.70
Data Engineer 1commonmedium0.66
Entry-Level Data Engineercommonmedium0.70
Junior Data Engineercommonmedium0.68
Associate Data Engineercommonmedium0.60
Data Engineering Entry/Midcommonmedium0.60
P1–P4commonmedium0.50

Classification mappings

O*NET / SOC

  • code=15-0000title=Computer & Mathematical Occupationssource=inferred_from_superfunctionreviewStatus=needs_review