Tech & Engineering SMB (51-200 employees)

Data Engineer at SMB

Data pipeline architect: designs and maintains the infrastructure that turns raw data into reliable assets for analytics and ML.

In SMBs, communication with non-technical areas is as important as technical ability

Moderate-to-high agreeableness is key to navigating informal structures

Assess experience managing external vendors, since they're a regular part of the functional team

Generic profile Startup (1-50 employees) Enterprise (201-1000 employees) Global (1001+ employees)

Ideal OCEAN+ Profile

Openness 75 Conscientiousness 76 Extraversion 45 Agreeableness 54 Emotional Stability 75 Structure & Rhythm 78
Ideal range
Openness
67 83

At SMBs (51-200 employees), technical curiosity to explore new architectures

Conscientiousness
68 83

At SMBs (51-200 employees), discipline in code and development processes

Extraversion
35 55

At SMBs (51-200 employees), collaboration with technical teams and stakeholders

Agreeableness
45 63

At SMBs (51-200 employees), the balance between defending technical decisions and accepting feedback

Emotional Stability
67 83

At SMBs (51-200 employees), resilience in the face of production bugs and deadline pressure

Structure & Rhythm
70 85

At SMBs (51-200 employees), effective communication with the team

Strengths and Red Flags

Strengths

  • Design of scalable, reliable data architectures
  • Methodical debugging of complex pipelines and data quality issues
  • Balance between modernizing existing systems and keeping operations running without disruption
  • Ability to justify technical investments to non-technical stakeholders using business language

Red Flags

  • Building pipelines without tests or quality monitoring
  • Resistance to documenting data transformations for other teams
  • Demands big-company tools and budget to operate
  • Chronic frustration over the lack of clear separation between roles and responsibilities

Interview Questions

Tell me about a data pipeline that failed silently in production. How did you detect it, and what mechanisms did you implement afterward?

Evaluates: Conscientiousness and Emotional Stability in the face of silent failures

Describe a data architecture you designed from scratch. What trade-offs did you evaluate and how did you communicate them to the team?

Evaluates: Openness and Conscientiousness in technical decisions

How did you prioritize technical improvements when the budget was limited and delivery couldn't stop?

Evaluates: Conscientiousness applied to realistic prioritization with limited resources

How did you explain an architecture decision to a general manager without technical training?

Evaluates: Extraversion and Agreeableness in translating technical topics into business language

More about Data Engineer

Career path, personality archetypes and similar roles in the full profile.

Career Path Archetypes Similar Roles Case Study

This Role in Other Contexts

Generic profile

Data Engineer — base profile with no company context

View profile → Startup (1-50 employees)

In startups, this role often covers broader responsibilities than its formal description

View profile → Enterprise (201-1000 employees)

In enterprise, the ability to work within regulatory frameworks without seeing them as a personal obstacle is a differentiator

View profile → Global (1001+ employees)

In global roles, advanced written technical English is a baseline requirement

View profile →
View all profiles for SMB →
Professional Services → All solutions →

Does your next Data Engineer at SMB (51-200 employees) match this profile?

Map anyone's OCEAN+ profile with the Talent Diagnostic: free, no signup, 10 minutes.

Take the free Talent Diagnostic Explore the Leadership Team Alignment Study

20 statements · 10 minutes · no card