Table 1Transition record

data engineertodata quality specialist

A data engineer already meets 17% of what the data quality specialist role asks for. The move turns on 16 required skills not yet in the profile.

From data engineer

17%

Overlap1

To data quality specialist

6 Skills carried over

16 Required, not held

81.7 Difficulty2

adjacent 0–30

moderate 30–55

substantial 55–75

career change 75–100

this move, 81.7

This move: 81.7 of 100 · career change

1 Share of the data quality specialist role’s weighted skill requirement already met by the data engineer profile. Required skills count in full, supplementary skills at 0.35. Directional: the figure for the reverse move differs. 2 Combines what is missing with how specialised it is, so a gap of general skills scores easier than the same number of narrow ones.

Table 2

Table 2 · What you already bring

Of the 6 skills that carry over, these are the ones fewest other occupations ask for. A data quality specialist role needs them, and most people applying for one will not have them already. This is the part of a data engineer background worth leading with.

Skill the target role also needs Area

already held establish data processes working with computers
already held design database in the cloud communication, collaboration and creativity
already held use data processing techniques working with computers
already held manage data information skills
already held process data information skills
already held statistics natural sciences, mathematics and statistics

All 6 carried skills, including the 4 the data quality specialist role treats as required.

Table 3

Table 3 · What you would need to learn

The 34 missing skills fall into 8 areas of the ESCO skill hierarchy, numbered below in the order worth working in: the areas carrying the most required skills come first, and inside each one the required skills sit above the supplementary ones.

Skill to acquire Tier

01 information and communication technologies (icts) 4 required, 7 supplementary

required, not held information structure required
required, not held query languages required
required, not held resource description framework query language required
required, not held database required

optional, not held LDAP optional
optional, not held LINQ optional
optional, not held MDX optional
optional, not held N1QL optional
optional, not held SPARQL optional
optional, not held XQuery optional
optional, not held data engineering optional

02 working with computers 4 required, 1 supplementary

required, not held utilise regular expressions required
required, not held normalise data required
required, not held implement data quality processes required
required, not held perform data cleansing required

optional, not held perform data analysis optional

03 information skills 3 required, 2 supplementary

required, not held handle data samples required
required, not held manage database required
required, not held report analysis results required

optional, not held execute ICT audits optional
optional, not held execute analytical mathematical calculations optional

04 communication, collaboration and creativity 2 required, 2 supplementary

required, not held design database scheme required
required, not held address problems critically required

optional, not held build business relationships optional
optional, not held train employees optional

05 management skills 2 required, 2 supplementary

required, not held define data quality criteria required
required, not held manage standards for data exchange required

optional, not held manage schedule of tasks optional
optional, not held perform project management optional

06 arts and humanities 1 required, 1 supplementary

required, not held data ethics required

optional, not held visual presentation techniques optional

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a data quality specialist role is least likely to hire without. The ordering is computed from the skill data, not from what pays.

Each entry opens a course search for that skill. Career Overlap earns nothing from these links.

Appendix

Appendix · The rest of the record

All 6 skills that carry over

Skill Type

already held establish data processes skill
already held manage data skill
already held process data skill
already held use data processing techniques skill
already held design database in the cloud skill
already held statistics knowledge

The 2 learning areas not shown above

Skill to acquire Tier

07 business, administration and law 2 supplementary

optional, not held data quality assessment optional
optional, not held business processes optional

08 health and welfare 1 supplementary

optional, not held healthcare analytics optional

18 supplementary skills, helpful but not required

Skill to acquire Tier

optional, not held LDAP optional
optional, not held LINQ optional
optional, not held MDX optional
optional, not held N1QL optional
optional, not held SPARQL optional
optional, not held XQuery optional
optional, not held data quality assessment optional
optional, not held execute ICT audits optional
optional, not held healthcare analytics optional
optional, not held visual presentation techniques optional
optional, not held build business relationships optional
optional, not held business processes optional
optional, not held data engineering optional
optional, not held execute analytical mathematical calculations optional
optional, not held manage schedule of tasks optional
optional, not held perform data analysis optional
optional, not held perform project management optional
optional, not held train employees optional

22 held skills the data quality specialist role does not ask for

Skill Type

not needed by the target role SAS Data Management knowledge
not needed by the target role Teradata Database knowledge
not needed by the target role analyse pipeline database information skill
not needed by the target role cloud technologies knowledge
not needed by the target role computer science knowledge
not needed by the target role create data models skill
not needed by the target role create data sets skill
not needed by the target role data analytics knowledge
not needed by the target role data models knowledge
not needed by the target role data storage knowledge
not needed by the target role data warehouse knowledge
not needed by the target role database management systems knowledge
not needed by the target role develop data processing applications skill
not needed by the target role digital data processing skill
not needed by the target role implement data warehousing techniques skill
not needed by the target role manage ICT data architecture skill
not needed by the target role manage quantitative data skill
not needed by the target role manage research data skill
not needed by the target role perform dimensionality reduction skill
not needed by the target role store digital data and systems skill
not needed by the target role unstructured data knowledge
not needed by the target role use databases skill

16 gaps that are knowledge rather than practice

Knowledge gaps usually close through study. Practical skill gaps usually need something you can point at.

Skill to acquire Tier

required, not held information structure required
required, not held query languages required
required, not held resource description framework query language required
required, not held data ethics required
required, not held database required
optional, not held LDAP optional
optional, not held LINQ optional
optional, not held MDX optional
optional, not held N1QL optional
optional, not held SPARQL optional
optional, not held XQuery optional
optional, not held data quality assessment optional
optional, not held healthcare analytics optional
optional, not held visual presentation techniques optional
optional, not held business processes optional
optional, not held data engineering optional

Index

Other moves recorded from data engineer

Full index of moves from data engineer

Note

How this record was compiled

Both occupations are taken from ESCO, which lists the skills and knowledge each occupation is expected to have and marks every one required or optional. Nothing here is a prediction about hiring, and nothing here knows that a particular employer wants a particular certificate. Treat Table 3 as a starting point for your own research rather than a syllabus. The full method states what these figures can and cannot tell you.