Data & Analytics

Graduate Data Engineer

₹5–12 LPA

Entry level · 0–1 years · Hybrid · Gig or permanent · Indicative CTC, India

Capability

PipelinesSQLReliability

Disposition & behaviour

ConscientiousnessScepticismExplaining to non-experts

Take the qualification testQualify once. Your verified profile goes to employers hiring for this role.

GoMeasure Platform runs GoMeasure Campus — a talent network for final-year students and new graduates, where what you can do is measured from real work rather than claimed on a CV.

We’re looking for Graduate Data Engineers to join this network ahead of the placement cycle. Move and reshape data between systems with pipelines that survive schema drift and failure.

You’ll take one qualification test covering pipelines, sql, reliability, build a verified profile, and go to the employers hiring into this track — typically ₹5–12 LPA at entry level.

Role summary

Move and reshape data between systems with pipelines that survive schema drift and failure.

What you will do

In the first six months

Build and maintain pipelines that move data between systems
Fix the breakages, which arrive when an upstream schema changes without warning
Learn the warehouse and how its models are structured
Write the checks that catch bad data before anyone builds a report on it

By twelve to eighteen months

Own a pipeline and its reliability, including the alerting
Design data models other teams then depend on
Work with analysts on what they actually need rather than what they asked for

Required skills

SkillWhat good looks like at entry level

SQLDeeper than an analyst needs — query performance, execution plans and why a join is slow at scale.

PythonThe default language for pipeline work. Scripting competence plus enough software discipline to write code that can be maintained.

Pipeline designIdempotency, retries and what happens when a job runs twice. Most data incidents are reruns that were not designed for.

Data modellingStructuring data so the questions people will ask are answerable. Getting this wrong is expensive and slow to undo.

ReliabilityMonitoring, alerting and the discipline of knowing a pipeline failed before the business tells you.

Disposition & traits

Skills describe what someone can do when they try hardest. Disposition describes what they typically do — and over a first year, that second question predicts as much as the first. For this track the dispositions that matter most are:

Conscientiousness
Scepticism
Explaining to non-experts

How to read these. Higher is not automatically better — a disposition that helps in one role works against another. These are not a pass mark, not trainable in the way a skill is, and never reported on their own.

Eligibility — who actually gets to apply

Fewer dedicated graduate openings than analyst roles — most data engineers arrive via a software or analyst track rather than straight from campus. That makes it a strong second move rather than a first job for many people, and the demand is real enough that the route is worth planning for.

Eligibility is set per drive and your placement cell’s notice is what actually applies on your campus. One trap worth knowing: a 6.0 CGPA is not always 60%. Where a university converts with (CGPA − 0.75) × 10, a 6.0 is 52.5% — below most employers’ floor. Check which formula yours uses before assuming you qualify.

And on the package: CTC is not take-home. A ₹4 LPA offer lands nearer ₹28,000–32,000 a month once provident fund, gratuity and tax come out, and offers with a large variable or joining-bonus component differ more again. Compare offers on fixed monthly pay, not on the headline. On-campus mass recruiters rarely move off a standard package; startups, GCCs and mid-size firms hiring off-campus often have some room.

Who should apply

Graduates whose degree and interests line up with the work above. Eligibility aside, employers in this track screen on demonstrated capability more than on which campus you attended.

This role is probably not for you if you want to work on the analysis itself. Data engineering is infrastructure — you build what the analysts stand on, and your work is invisible when it is going well.

Evaluation notice

Results are shared with the student and, with consent, with employers hiring into this track. Scores carry the evidence and the assessment date. Practice and assessed sessions are clearly distinguished before either begins.

What you get back

The outcome of qualifying is a report, not a pass mark. Three layers, each scored and reported separately — there is no single number, deliberately, because a composite hides the trade-off an employer actually needs to see.

01 · Capability

What you can do at your best

Role-specific skills and real work, placed on a proficiency level with the evidence attached.

PipelinesSQLReliability

02 · Disposition

What you typically do

How you tend to work, and the judgement you show in realistic situations. Not a pass mark, and higher is not automatically better.

ConscientiousnessScepticismExplaining to non-experts

03 · Alignment

What you are optimising for

What you want from work, and whether a role supplies it. Read as fit rather than quality.

Fit, not good or bad

Who sees it

Every layer carries its own score, its weighting and the date it was assessed — and you see the same report the employer does. The report is shared with employers hiring into this track, with your consent, and you can withdraw it. Individual employers are named on the drive itself, once that employer is participating.

Retaking the test

One qualification attempt per track, with a retake available after one to two months. The wait is deliberate: a retake a week later measures how well you remember the test, not whether anything changed. The gap is long enough for preparation against your reported gaps to actually show.

Get placed in this track

One qualification test puts you in the talent pool for this role, with a verified profile that employers can act on — instead of a CV that looks like every other CV in the stack.

Join the talent pool