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Data Engineer

DENG.GEN.P2

P2P2 — Developing Professionalmedium0.70draftglobalv1

Data Engineers design and own complex pipelines and data storage solutions.

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

Data Engineers design and own complex pipelines and data storage solutions.

Level — P2 — Developing Professional

Early-career professional; developing skills, handles routine tasks with some independence

Scope
Defined deliverables / small features
Autonomy
General supervision; reviewed at milestones
Complexity
Some non-routine problems; applies established patterns
Impact
Own and immediate-team deliverables
Decision rights
Routine technical choices within guidance
Leadership
May guide interns
Typical experience
1–3 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

Responsibilities8

  • Design and own complex pipelinescommonlevel
  • Ensure data qualitycommonlevel
  • Optimize data storage solutionscommonlevel
  • Implement data security measurescommonlevel
  • Collaborate with data scientists to support advanced analyticscommonlevel
  • Develop and maintain ETL processescommonlevel
  • Conduct performance tuning of data systemscommonlevel
  • Document and improve data engineering processescommonlevel

Tasks5

  • Design complex data pipelines.commonlevel
  • Ensure data quality.commonlevel
  • Optimize storage solutions.commonlevel
  • Implement security measures.commonlevel
  • Support analytics.commonlevel

Skills8

  • Big data toolscommonlevel
  • Data warehousingcommonlevel
  • ETL developmentcommonlevel
  • Data quality assurancecommonlevel
  • Data securitycommonlevel
  • Performance tuningcommonlevel
  • Process documentationcommonlevel
  • Advanced SQLcommonlevel

Knowledge8

  • Big data technologiescommonlevel
  • Data warehousingcommonlevel
  • ETL processescommonlevel
  • Data security practicescommonlevel
  • Performance optimizationcommonlevel
  • Advanced SQL techniquescommonlevel
  • Data governancecommonlevel
  • Analytics supportcommonlevel

competency8

  • Proficiency with big data toolscommonlevel
  • Data warehousing conceptscommonlevel
  • Analytical thinkingcommonlevel
  • Problem-solvingcommonlevel
  • Attention to detailcommonlevel
  • Communicationcommonlevel
  • Project managementcommonlevel
  • Data securitycommonlevel

qualification5

  • Proficiency with big data toolscommonlevel
  • Designed a data pipeline end-to-endcommonlevel
  • Bachelor’s degree in Computer Science or related fieldcommonlevel
  • 2-4 years of experience in data engineeringcommonlevel
  • Certification in big data technologiescommonlevel

Title aliases

AliasTypeConfidenceApproved
Data Engineering IIcommonmedium0.70
Data Engineering 2commonmedium0.66
Data Engineer IIcommonmedium0.70
Data Engineer 2commonmedium0.66
Data Engineercommonmedium0.50

Classification mappings

O*NET / SOC

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