Join a project shaping the future of sustainable energy through cutting‑edge data engineering and scientific innovation. We are looking for a Data Engineer to help build scalable cloud-native data platforms for a deep‑tech Customer working on one of the most ambitious fusion energy initiatives in the world.
You will work with modern distributed data technologies, including Databricks, Apache Spark, AWS, and Azure, while solving complex engineering challenges in a research‑intensive environment.
We at Sigma Software value engineering excellence, long‑term partnerships, and continuous learning. This is an opportunity to contribute to breakthrough scientific initiatives while working with modern technologies and highly skilled general teams.
PROJECTThe project focuses on building and evolving a modern cloud‑based data platform supporting scientific research, analytics, and operational workflows in the fusion energy domain. The team develops scalable distributed data processing solutions while ensuring high standards of data quality, lineage, governance, reproducibility, and operational reliability.
You will work closely with scientists and engineers to support experimentation, analytics, and machine learning workflows in a highly innovative R&D; environment. Job Descriptio Design, develop, and maintain scalable and reliable data platforms and pipelines for analytics and operational use caseBuild distributed data processing workflows using Apache Spark, py Spark, and DatabricDevelop and evolve cloud-native data solutions leveraging Azure and AWS servicesModel and optimize data structures for analytics, reporting, and downstream consumptionIntegrate data from multiple heterogeneous sources while ensuring data quality, consistency, and traceabilityImplement data quality controls, schema validation, lineage tracking, and monitoring processesOptimize performance, scalability, reliability, and cost‑efficiency of data pipelines and infrastructureCollaborate closely with scientists, analysts,



and engineering teams to translate business and research requirements into technical solutionsContribute to CI/CD processes, infrastructure automation, and engineering best practicesResearch and introduce new technologies and approaches within the data engineering ecosystem ecosystem Qual 3+ years of commercial experience in Data Engineering2+ years of hands‑on production experience with DatabricksStrong expertise with Delta Lake, including medallion architecture and table optimizationAdvanced proficiency in Python, py Spark, and SQLDeep practical knowledge of Databricks components including Unity Catalog, Lakeflow Jobs / Workflows, and job optimizationHands‑on experience with AWS services including S3, IAM, KMS, and at least one of AWS Batch, ECR, Event Bridge, Lambda, or API GatewayExperience designing event‑driven and asynchronous data pipelinesStrong knowledge of Infrastructure as Code and CI/CD practicesPractical experience with Terraform and Databricks Asset BundlesExperience working with Git workflows, pull request reviews, and automated testingUnderstanding of secure authentication approaches such as OIDC and service principalsPractical experience with MLflow, experiment tracking, model registry, and reproducibility practicesStrong understanding of data quality, lineage, schema contracts, and provenance conceptsExperience with data quality frameworks such as Great Expectations, Soda, py Deequ, or Databricks DQXExperience monitoring and optimizing data platform reliability and cloud costsUpper-Intermediate or higher English level WILL BE A PLUS: Experience packaging workloads using Docker and running batch workloads in AWSFamiliarity with ECR and containerized data processing solutionsExperience with experiment optimization libraries such as scikit‑optimize, Bo Torch, Ax, or scipyUnderstanding of ML feature engineering and leakage prevention techniquesExperience working in regulated or high‑security environmentsKnowledge of data governance, compliance, and data residency requirementsExperience disabling or restricting AI‑assisted tooling/ features in secure environments

📌 Data Engineer (Madrid)
🏢 Sigma Software
📍 Madrid