GWI

Data Engineer

Athens, GR

Actively hiring, first seen by us today

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time · Permanent — employment source
Weekly office requirement: Hybrid, 1 day/week Employment type: Permanent, full-time, employee Linked Seniority level: Mid-Senior Every business is using AI. The ones that get it right start with real people. GWI is the human intelligence underneath: verified data that helps businesses understand what moves their audience, and act on it faster. If you want your work to matter, keep reading.
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What you’ll work on

Full posting

Build and run reliable, well-monitored data pipelines and warehouse
Design analytics-ready data models with clear lineage and documentation
Optimise warehouse cost and performance through query tuning
Manage data access so people and AI assistants can use trusted data

From the employer’s posting

Building and running reliable, well-monitored data pipelines, infrastructure and warehouse

Designing analytics-ready data models with clear lineage and documentation

Optimising warehouse cost and performance through query tuning

Managing data access so the right people and AI assistants can securely find, understand and use trusted, well-documented data

What you’ll bring

All qualifications

Core experience

Proficiency in SQL and Python
Hands-on end-to-end pipeline experience on a cloud data stack (BigQuery, Airflow, dbt or equivalents)
Engineering practices: Git, code reviews, testing, documentation and CI/CD
Knowledge of data accessibility, cataloguing and quality assurance
Ability to scope and deliver work independently in an Agile environment

Qualification wording

with proficiency in SQL and Python

hands-on experience with ingestion, orchestration, modelling, transformation and data quality on a cloud data stack, such as BigQuery, Airflow and dbt (or equivalents)

Git, code reviews, testing, documentation and CI/CD

knowledge of data accessibility, cataloguing and quality assurance

you can scope, estimate and deliver work independently in an Agile environment

Apply at GWI

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 4, 2026today
Recorded sightings: 1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

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From 10,736 similar postings that came down. Coming down is not always a hire.

GWI is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
BigQuery
dbt
Airflow

Where the posting names them

You’ll need to be able to demonstrate the core skills this role requires. You don’t have to tick all the boxes right away; the important thing is that you’re willing to learn. - Data engineering experience: a strong track record of impactful delivery as a Data or Analytics Engineer, with proficiency in SQL and Python. - End-to-end pipelines: hands-on experience with ingestion, orchestration, modelling, transformation and data quality on a cloud data stack, such as BigQuery, Airflow and dbt (or equivalents).

- Data engineering experience: a strong track record of impactful delivery as a Data or Analytics Engineer, with proficiency in SQL and Python. - End-to-end pipelines: hands-on experience with ingestion, orchestration, modelling, transformation and data quality on a cloud data stack, such as BigQuery, Airflow and dbt (or equivalents). - Engineering practices: Git, code reviews, testing, documentation and CI/CD, plus comfort using AI-assisted development tools while reviewing and testing their output with care.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Weekly office requirement: Hybrid, 1 day/week
Employment type: Permanent, full-time, employee
Linked Seniority level: Mid-Senior

Every business is using AI. The ones that get it right start with real people. GWI is the human intelligence underneath: verified data that helps businesses understand what moves their audience, and act on it faster. If you want your work to matter, keep reading.

What will I be doing?

As our Data Engineer you’ll maintain and enhance the Business Data Platform that sits at the heart of our BI Engineering team, serving analytics built on GWI’s internal data to the wider business so it can make confident decisions. You’ll work closely with colleagues across GWI to keep pipelines dependable, data models clear and analytics-ready, and data securely accessible across dashboards and AI tooling.

The accuracy and accessibility of our data shape how we measure performance, plan ahead and adopt AI-assisted analytics, so your work directly supports GWI’s goal of putting consumer insights at the heart of every organisation.

A few things you’ll be responsible for:

Building and running reliable, well-monitored data pipelines, infrastructure and warehouse, backed by strong testing and data quality practices.
Designing analytics-ready data models with clear lineage and documentation, in close partnership with analysts and stakeholders.
Optimising warehouse cost and performance through query tuning, efficient data modelling and careful resource management.
Managing data access so the right people and AI assistants can securely find, understand and use trusted, well-documented data.

Working at GWI means a high tempo environment where change is common. We’re building quickly because the industry is moving quickly, and our customers rely on us to stay ahead. If you like being part of that, you’ll enjoy it here.

What do I need to bring with me?

You’ll need to be able to demonstrate the core skills this role requires. You don’t have to tick all the boxes right away; the important thing is that you’re willing to learn.

Data engineering experience: a strong track record of impactful delivery as a Data or Analytics Engineer, with proficiency in SQL and Python.
End-to-end pipelines: hands-on experience with ingestion, orchestration, modelling, transformation and data quality on a cloud data stack, such as BigQuery, Airflow and dbt (or equivalents).
Engineering practices: Git, code reviews, testing, documentation and CI/CD, plus comfort using AI-assisted development tools while reviewing and testing their output with care.
Data governance: knowledge of data accessibility, cataloguing and quality assurance.
Independence and collaboration: you can scope, estimate and deliver work independently in an Agile environment, and you communicate well with analysts and stakeholders.
A plus: exposure to preparing data for AI use cases, such as semantic and metrics layers, well-documented models, and LLM-based tooling (RAG, embeddings, vector databases).

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