Is Ilkka Ravensbourne a real engineer

No. The person is invented for this page, and so are Kaarmela Retail and Verlaakso Telecom. The figures show a shape and describe nobody's work.

Which numbers matter most for a data engineer

Runtime, cost and incident count. They map directly onto what a data platform lead is measured on, and all three are things you already know about your own pipelines.

Should the tool list include everything I have touched

Ten entries is enough. The example names ten and attaches five of them to an outcome in the experience lines, which is the part that makes a tool name evidence rather than a claim.

What did the checker score it

98 out of 100, re-measured on 25 September 2026, with readable volume 3 points short and achievement quality 1 point short. The arithmetic is 100 × 30% for parseability + 100 × 30% for completeness + 96 × 40% for content. The writing check beside it scored 95, which is 91 of the 96 points that applied, and the five it withheld are the bullet tense rule.

Is a runbook worth a line

Yes. Writing the on-call runbook for 30 pipelines and training six engineers on it is operational maturity, and it is the difference between someone who builds pipelines and someone who can be given the pager.

Which design is this rendered in

Architect, one of the eight layouts in the ATS family. The eight were chosen from a measurement taken on 2026-09-14: each exports a PDF whose text layer scores exactly what the pasted text scores, on both test documents, in one column, with the reading order kept and no graphics. It is a plain single column, which suits a document whose content is almost entirely figures.

Example · Data

A free data engineer résumé example, written in runtimes and cost

One complete data engineer résumé, written out in full. The person is invented. The reading and the score come from the product itself.

ConxfolioPublished 2026-09-13 · updated 2026-09-25

— a pipeline that runs is not news. one that got cheaper is.

The data engineer example résumé drawn as a complete page in the Architect design: name, summary, three dated roles with five achievement lines under each, education and a skills row — The example below, drawn by the builder's own renderer in the Architect design. The picture was taken by pressing this page's own Use this example door and photographing what the editor rendered.

Data engineering is full of work that is invisible until it breaks, and résumés in this field often describe the stack rather than the effect. This example is written out in full so you can read the effect version, then run through the tools here to see what a parser stores. The candidate is invented.

The example, in full

An invented person. Not a real document, and not yours.

Ilkka Ravensbourne
Data Engineer
Helsinki, Finland · [email protected] · +358 9 5550 0141

Summary
Data engineer with eight years building pipelines for retail and telecom operators in Finland, working on warehouse cost, data freshness and the quality tests that fire before a business team notices.

Experience

Senior Data Engineer · Kaarmela Retail, Helsinki · 2021 to present

Rebuilt the nightly warehouse load across 240 tables and cut the run from 5 hours to under 1 hour for 40 reporting teams.
Reduced warehouse cost by 37% a year by partitioning 9 of the 12 largest tables and rewriting the 6 reports behind them.
Introduced data quality tests on 180 models and cut incidents from 14 to 3 a quarter across 2 reporting years.
Moved 60 legacy scheduled jobs onto a single Airflow deployment over 8 months with no unplanned downtime for any of the 12 reporting teams.
Documented 40 core data models and trained 9 engineers on them, which removed 200 ad hoc questions a quarter from the team.

Data Engineer · Verlaakso Telecom, Tampere · 2017 to 2021

Built the event pipeline that carried 400 million records a day at 99.95% delivery across 4 years of continuous operation.
Cut pipeline failures by 52% by adding schema checks at ingestion on 30 sources and alerting the owning team directly.
Wrote the on-call runbook for 30 pipelines and trained 6 engineers on it, which halved the average incident to 40 minutes.
Modelled 90 telecom usage tables in the warehouse and delivered a billing data set that finance reconciled across 14 markets.
Automated the daily reconciliation between 6 source systems and returned 12 hours a week to 4 analysts in the finance team.

Data Analyst · Verlaakso Telecom, Tampere · 2015 to 2017

Produced 40 recurring reports a month for 3 business teams and cut the manual preparation behind them by 60% within 1 year.
Cleaned 2 million customer records against the address register and raised the match rate from 82% to 97% in 6 months.
Queried 12 source databases for the churn study and delivered the analysis that 3 product teams built their 2017 plan on.
Tested 300 figures in 20 reports against the source systems each quarter and found 20 errors before any reached a customer.
Learned SQL and Python on the job over 2 years and moved 9 manual spreadsheets onto a scheduled nightly pipeline.

Education
MSc Computer Science · Aurajoki Technical University, Turku · 2012 to 2017

Skills
Python, SQL, Spark, dbt, Airflow, Kafka, BigQuery, data modelling, cost optimisation, on-call

Languages
Finnish · native · English · C1 · Swedish · B1

Runtime, cost, incidents

A nightly load for 240 tables cut from five hours to under one. Warehouse cost down 37% after nine of the twelve largest tables were partitioned. Incidents from fourteen to three a quarter once 180 models carried data quality tests. Those three are the whole job stated in three sentences, and a platform lead recognises every one of them.

The migration line is the fourth kind: sixty legacy scheduled jobs moved onto one orchestrator with no unplanned downtime. Migrations are where trust is earned in this work, and the absence of an outage is the result worth reporting.

Scale lines still need a quality figure beside them

Four hundred million records a day is a scale claim, and on its own it describes a company rather than an engineer. The example attaches 99.95% delivery to it, which turns it into a statement about the pipeline that was built.

The schema check line works the same way: failures down 52% after checks were added at ingestion. It names a decision, and the decision has a number.

Skills for a data engineer résumé, grouped

Ilkka's skills split into languages, pipelines and platform. Languages: Python, SQL. Pipelines: Spark, dbt, Airflow, Kafka. Platform and practice: BigQuery, data modelling, cost optimisation, on-call. A data platform lead reads the pipeline group as your toolkit and the practice group as your maturity.

Engineers moving from analytics often keep a small analysis group too, with a BI tool or two. The free résumé builder prints named groups with a bold label, or one list if you prefer.

From data analyst to senior data engineer

The analyst role at Verlaakso shows a common route: queries written, reports automated, a data source cleaned up because nobody else would. The data engineer role changes the subject to pipelines: jobs built, runtimes cut, freshness targets kept.

Senior lines add cost and reliability as first-class results: spend reduced, incidents avoided, a model other teams now build on. Put a quality figure beside every scale figure, so a large pipeline does not read as a fragile one. The keywords guide explains how tool names are read by applicant tracking software.

How it reads and scores

The import review read three dated roles with five lines under each, one degree and ten skills, with three languages kept in their own section. The ATS checker scored it 98 out of 100, re-measured on 25 September 2026, with readable volume 3 points short and achievement quality 1 point short: 100 × 30% for parseability, 100 × 30% for completeness and 96 × 40% for content. The writing check scored it 95, which is 91 of the 96 points that applied here. How the reading and the score are produced is set out in the note on how these examples are made.

The Conxfolio import review after the door opened, showing Ilkka Ravensbourne's example read into fields beside the rendered page, with the line saying it is an example — Ilkka Ravensbourne's data engineer résumé read into fields, each field beside the line it came from.

The same import review on a 390 pixel phone screen, with the example notice above the accept button — Ilkka Ravensbourne's data engineer résumé in the same review on a 390 px phone.

What this example leaves off

No certification badges, no cloud vendor logos and no list of forty technologies. Ten skills is enough to match a posting, and a longer list dilutes the five that are attached to an outcome in the experience lines.

Architecture diagrams and repository links are left off as well. A platform lead will ask about architecture at interview, where the answer can be drawn and questioned. On paper, a runtime that fell from five hours to under one says more about the architecture than a diagram would.

What to change for your own

Change the stack and keep the structure. Batch, streaming, lakehouse and warehouse work all use this shape with different tool names, and the numbers stay in the same three families. Then put in your own runtimes, costs and incident counts.

Keep one operational line. Keep the languages if they matter where you are applying. The design gallery holds 37 layouts, and the data analyst example, the DevOps engineer example and the QA engineer example show the same structure beside it.

Write yours beside it

Opens the builder with Ilkka's example loaded, saved as its own entry in the Architect design. Replace every line with your own. Free, no account.

Use this example Check a résumé instead

Questions

Is Ilkka Ravensbourne a real engineer: No. The person is invented for this page, and so are Kaarmela Retail and Verlaakso Telecom. The figures show a shape and describe nobody's work.
Which numbers matter most for a data engineer: Runtime, cost and incident count. They map directly onto what a data platform lead is measured on, and all three are things you already know about your own pipelines.
Should the tool list include everything I have touched: Ten entries is enough. The example names ten and attaches five of them to an outcome in the experience lines, which is the part that makes a tool name evidence rather than a claim.
What did the checker score it: 98 out of 100, re-measured on 25 September 2026, with readable volume 3 points short and achievement quality 1 point short. The arithmetic is 100 × 30% for parseability + 100 × 30% for completeness + 96 × 40% for content. The writing check beside it scored 95, which is 91 of the 96 points that applied, and the five it withheld are the bullet tense rule.
Is a runbook worth a line: Yes. Writing the on-call runbook for 30 pipelines and training six engineers on it is operational maturity, and it is the difference between someone who builds pipelines and someone who can be given the pager.
Which design is this rendered in: Architect, one of the eight layouts in the ATS family. The eight were chosen from a measurement taken on 2026-09-14: each exports a PDF whose text layer scores exactly what the pasted text scores, on both test documents, in one column, with the reading order kept and no graphics. It is a plain single column, which suits a document whose content is almost entirely figures.

Conxfolio is a free set of four career tools: a résumé builder with 37 rendered layouts, an ATS résumé checker that prints its own arithmetic, a cover letter builder that traces every proof paragraph back to the line it came from, and a portfolio builder with 22 authored designs. There is no account to create, nothing is held back for a paid plan, and no language model is used anywhere in the product, so the readers, the score and the letter are deterministic code you can check.