Senior Data Engineer Greece

Our current work includes:

• Large-scale data processing - building robust ETL/ELT pipelines with Apache Spark that ingest, transform, and serve terabyte-scale multimodal datasets across the marketing intelligence stack.
• Polyglot data infrastructure - designing and operating relational databases for transactional workloads, vector databases for semantic search and RAG systems, and graph databases for audience relationship and attribution modelling.
• Data transformation and modelling - orchestrating analytics engineering workflows with dbt to create well-documented, tested, and version-controlled data models that power downstream AI and BI systems.
• Data platform reliability - building the data platform foundations (orchestration, monitoring, data quality checks, lineage tracking) that ensure our pipelines and databases are dependable under production load.

You will be a technical lead for the data services and infrastructure that turn raw data into reliable, well-modelled products: scoping the problem, choosing the architecture, building and shipping to production, and operating it under live traffic. You are not handing off a design to someone else - you ship what you build, and you set the bar for how it's built. You'll work closely with data scientists and software engineers across the stack.

What you'll be doing:

• Architect and build production data pipelines and data platforms that serve models, data, and AI workflows to internal and client-facing applications, accountable for them under live traffic.
• Own non-functional quality - latency and throughput budgets, scalability, reliability, observability, and cost - for the systems in your domain.
• Lead the design and operation of multi-model data stores - relational databases (PostgreSQL, MySQL), vector databases (Pinecone, Weaviate, pgvector), and graph databases (Neo4j, Neptune) - ensuring the right tool for each access pattern.
• Set technical direction: write design docs, make build-vs-buy decisions, and defend your approach with evidence.
• Work across the stack when needed - services, data access, infrastructure-as-code, CI/CD - and debug it when things drift in production.
• Mentor and set the quality standards for mid-level and junior data engineers.

• 5+ years of professional software engineering experience, shipping and operating production systems - you've dealt with scaling, reliability, on-call, and the gap between a working prototype and a dependable service.
• Deep, demonstrable expertise designing and building distributed data pipelines with Apache Spark, and strong data modelling across relational, vector, and graph databases.
• Strong proficiency in at least one general-purpose language (e.g., Python, Scala, or Java) and the ability to work effectively across others.
• Hands-on experience with cloud platforms (GCP/AWS), containers (Docker), CI/CD, and infrastructure-as-code (Terraform).
• Strong software engineering habits - version control, testing, code review, CI/CD.
• Comfort with ambiguity. Many of our problems don't have a known-good solution.
• Clear communication - you can write a one-page design doc that is useful for both product managers and staff engineers.

If you know some of this, even better:

• Experience building and operating ML/LLM-powered production systems (model serving, RAG, agents) at scale.
• Experience with event-driven or streaming architectures (e.g., Pub/Sub, Kafka) and real-time systems.
• Depth in security, IAM, networking, and data governance in cloud environments.
• Background in marketing technology, ad tech, or large-scale data products.
• Meaningful open-source contributions or a track record of technical leadership.

Pulled from the full job description Paid volunteer time Flexible schedule, * 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.

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.