Level

Satalia

Data Engineer – Mid Level Greece

AI in this role

Build and maintain production data pipelines and models to support data science, analytics, and AI workflows.

pineconeweaviatepgvectordbtpostgresql
ragdata-engineeringetldata-modelingsqldata-warehousing

Data Engineer – Mid Level Greece

Role type: Permanent

Location: Greece

Data Engineer required to join our Satalia team in Greece

As an organisation, we push the boundaries of data science, optimisation and artificial intelligence to solve the most complex problems in the industry. Satalia, a WPP company is a community of individuals devoted to working on diverse and challenging projects, allowing you to flex your technical skills whilst working with a tight-knit team of high performing colleagues.

Led by our founder and WPP Chief AI Officer Daniel Hulme, Satalia’s ambition is to become a decentralised organisation of the future. Today, this involves developing tools and processes to liberate and automate manual repetitive tasks, with a focus on freedom, transparency and trust. At the core of our thinking is an approach to wellbeing and inclusivity. We unpack human behaviour and unpick prejudice to ensure a safe and inviting environment. We offer truly flexible working and allow our employees to find the working practice that makes them most productive. At Satalia, your opinion matters and your achievements are celebrated.

The Role:

You'll build and own the pipelines and data models that turn raw data into clean, reliable, well-documented datasets — the foundation our data scientists, analysts, and AI systems build on.

Our current work includes:

• Building data pipelines — robust ETL/ELT pipelines that ingest, transform, and serve large datasets across our marketing intelligence stack.

• Data modelling and transformation — designing well-documented, tested, version- controlled data models (with dbt) that power downstream AI and BI.

• Warehouse and storage design — modelling data in our warehouse/lakehouse and relational databases, choosing the right structure for each access pattern.

• Trustworthy data — orchestration, monitoring, data quality checks, and lineage so the data people depend on is correct and dependable.

  • You'll work closely with data scientists and software engineers, own your pipelines end to end, and help shape how we build data at Satalia.

What you'll be doing:

• Design, build, and maintain production data pipelines that deliver clean, reliable data to analytics, BI, and AI workflows.

• Build SQL-based data transformations and models into well-documented, tested datasets that others can trust and reuse.

• Design and operate our data warehouse/lakehouse and relational databases (e.g. PostgreSQL) for the way the data is actually used.

• Build data-quality, monitoring, and lineage into pipelines so problems are caught early.

• Contribute to pipeline infrastructure — orchestration, CI/CD, and infrastructure-as- code — for the data platform.

• Share what you know with the rest of the team.

What we want from you:

• 4+ years building and running production data pipelines and data models.

• Strong SQL and data modelling, including SQL-based transformation (dbt or similar), and solid experience with a data warehouse or lakehouse.

• Strong Python (Scala or Java a plus), with good software engineering habits — version control, testing, code review, CI/CD.

• Experience with pipeline orchestration (Airflow, Dagster, or similar).

• Hands-on experience with a cloud platform (GCP or AWS).

• Clear communication — you can write a short design doc that's useful to both product managers and engineers.

Nice to have:

• Distributed data processing at scale (Apache Spark or similar).

• Containers (Docker) and infrastructure-as-code (Terraform).

• Experience with vector databases (Pinecone, Weaviate, pgvector) or graph databases (Neo4j, Neptune).

• Exposure to ML/LLM-powered data systems (RAG, embeddings, feature/serving pipelines).

• Event-driven or streaming data (Pub/Sub, Kafka) and real-time pipelines.

What we Offer:
  • Benefits - healthcare

  • Remote working - café, bedroom, beach - wherever works;

  • Truly flexible working hours - school pick up, volunteering, gym;

  • Generous Leave – inline with Greek Labour Law

  • Impactful projects - focus on bringing meaningful social and environmental change;

  • People oriented culture - wellbeing is a priority, as is being a nice person;

  • Transparent and open culture - you will be heard;

  • Development - focus on bringing the best out of each other;

Satalia is home to some of the brightest minds in AI and if you’re looking to join a company who not only values autonomy and freedom, but embraces a culture of inclusion and warmth, we’d love to hear from you.

We aim to respond to all applications within 2 weeks. If you have not heard from us within 2 weeks this means your application has been unsuccessful.

By applying to Satalia you are expressly giving your consent for the collection and use of your information as described within our Satalia Recruitment Privacy Policy.

Good luck!

How we rate this

Data Engineer – Mid Level Greece at Satalia rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGData EngineeringETLData ModelingSQLData WarehousingPineconeWeaviate

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Tell me about a project where data engineering was part of your work. What did you do?
  3. Tell me about a project where etl was part of your work. What did you do?
  4. Tell me about a project where data modeling was part of your work. What did you do?
  5. Tell me about a project where sql was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, Data Engineering, ETL, Data Modeling, and SQL. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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