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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer | 100% remote - **Company:** UST - **Location:** Madrid, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Audit Trail, Automation of Tests, Cloud Database, Continuous Integration, Data Integrity, Extract Transform Load (ETL), Data Profiling, Data Systems, Database Queries, Document-Oriented Databases, Python (Programming Language), Performance Tuning, Reference Data, Transaction Data, Git, Data Management, Data Pipelines - **Published:** July 30, 2026 - **Apply:** https://es.indeed.com/viewjob?jk=b56b6eea70de76ab ## About the Role We are looking for a Data Engineer with strong experience in data migrations, SQL, Python, ETL/ELT pipelines, and AWS, capable of delivering secure, high-quality, and fully reconciled data solutions. Experience with large-scale customer and financial data migrations is essential. This is a 100% remote position based in Spain. Required experience and skills * Strong SQL skills across data profiling, complex transformation, reconciliation, performance analysis and relational modelling. * Strong Python or comparable data-engineering experience for repeatable pipeline and validation development. * Experience delivering large enterprise data migrations involving customer, contract, financial or transactional data. * Hands-on experience with ETL/ELT patterns, staging models, restartability, error handling, auditability and controlled reprocessing. * Experience defining and automating data-quality checks, reconciliation controls and migration evidence. * Working knowledge of cloud data services and object storage, preferably in AWS. * Experience with Git, CI/CD, environment promotion and automated testing for data pipelines. * Understanding of privacy, security, retention and access-control requirements for customer and financial data. * Ability to collaborate with business owners, architects, developers and testers to resolve ambiguous or poor-quality legacy data. * Strong written and spoken English and the discipline to maintain clear technical and operational documentation. ## Description * Profile source platforms and document data inventories, ownership, lineage, quality risks, retention constraints and extraction approaches. * Design source-to-target mappings and transformation rules for customer, account, contract, product, tariff, premise or supply point, meter, read or usage, bill, payment, balance, debt, interaction and reference data. * Build parameterised ETL/ELT pipelines for extraction, cleansing, standardisation, transformation, validation, loading and replay. * Implement data-quality controls for completeness, validity, uniqueness, referential integrity, effective dating, sequencing and cross-domain consistency. * Create reconciliation frameworks using record counts, control totals, financial balances, sampled journeys and exception reports across source, staging, target and downstream systems. * Partner with Business Analysts and utility SMEs to define remediation rules, ownership and acceptable tolerances for legacy-data issues. * Support iterative migration rehearsals, defect analysis, reprocessing, performance tuning and evidence-based readiness decisions. * Engineer cutover loads, delta or change-data capture approaches, freeze-window controls, rollback support and restartable processing. * Protect personally identifiable and financial data through least-privilege access, encryption, masking, secure transfer, audit logging and controlled retention. * Expose actionable pipeline metrics, logs, s and exception queues so failures can be diagnosed and recovered within the cutover window. * Support operational and analytical integrations to data platforms, reporting services and downstream consumers without compromising the system-of-record controls. * Document mappings, code, runbooks, reconciliation evidence, known exceptions and support procedures; transition ownership to production teams. ## 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) - [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) - [Resilient by Design: Building Robust Architectures in High-Stakes Financial Systems](https://www.wearedevelopers.com/videos/2106-resilient-by-design-building-robust-architectures-in-high-stakes-financial-systems) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [How One Developer Built the Back Office for 10 Million Companies](https://www.wearedevelopers.com/videos/100082-how-one-developer-built-the-back-office-for-10-million-companies) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Find a Developer Job: 12 Best Job Sites For Developers](https://www.wearedevelopers.com/magazine/165-find-a-developer-job-12-best-job-sites-for-developers) - [The Best Job Search Websites of 2025](https://www.wearedevelopers.com/magazine/368-the-best-job-search-websites-of-2025) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)