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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer Greece - Mid Level - **Company:** Satalia - **Location:** London, UK (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Big Data, Code Review, Databases, Continuous Integration, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Stores, Relational Databases, Graph Database, Identity and Access Management, Python (Programming Language), Operational Databases, Search Technologies, Datadog, Data Logging, Cloud Platform System, Large Language Models, Apache Spark, Git, Data Lineage, Apache Kafka, Codebase, Machine Learning Operations, Terraform, Data Pipelines, Automation Anywhere, Docker - **Published:** July 19, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=8496197d55b844fd ## About the Role * 2-4 years of professional data engineering experience, with work deployed to production. * Strong proficiency in at least one general-purpose language (e.g., Python, Scala, or Java) and comfort working across a codebase. * Solid fundamentals in designing and building data pipelines (ETL/ELT), with experience in Apache Spark for large-scale data processing. * Experience with cloud platforms (GCP/AWS), containers (Docker), and CI/CD. * Strong software engineering practices - Git, testing, code review, CI/CD. * Clear communication - you can explain technical choices and trade-offs to both technical and non-technical colleagues., * Experience integrating ML/LLM systems into production applications (model serving, RAG, agents). * Familiarity with infrastructure-as-code (Terraform), orchestration, and observability tooling. * Experience with event-driven or streaming architectures (e.g., Pub/Sub, Kafka). * Exposure to security, IAM, and data governance in cloud environments. * Background in marketing technology, ad tech, or large-scale data products. ## Description 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 - working with 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 - using 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 build and operate the services, APIs, and infrastructure that turn our models and data into reliable products, working closely with data scientists and data engineers to ship and run systems in production. You'll have real ownership of your work - designing services, shipping code, and operating what you build - with guidance from senior engineers who will help you grow technically. What you'll be doing: * Design, build, and maintain data pipelines that serve models, data, and AI workflows to internal and client-facing applications. * Work across database types - relational, vector, and graph - to model and store data appropriately for each access pattern, in partnership with data scientists. * Build and maintain dbt models - writing transformation logic, tests, and documentation that ensure data quality and traceability. * Operate what you build: instrument pipelines with logging, metrics, and tracing, and help diagnose and resolve production data issues. * Write clean, tested, production-quality code and contribute to CI/CD pipelines and infrastructure-as-code. * Participate in code reviews, design discussions, and retrospectives. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The OpenTelemetry mistakes I keep seeing (and how to stop making them)](https://www.wearedevelopers.com/videos/100158-the-opentelemetry-mistakes-i-keep-seeing-and-how-to-stop-making-them) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Accelerating Authentication Architecture: Taking Passwordless to the Next Level](https://www.wearedevelopers.com/videos/733-accelerating-authentication-architecture-taking-passwordless-to-the-next-level) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)