Desarrollador/a Fullstack

Tendios

. Own Tendios data end to end, from scraping through customer-facing products and AI features .

Posted 9/23/2026full-timeBarcelona • SpainMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data-driven features, managing data quality, and developing production data pipelines using Python and TypeScript. Proficient in leveraging LLM applications and maintaining data governance in complex systems.

Highest-signal resume keywords

Python ProgrammingPostgreSQL Database ManagementData Pipeline DevelopmentElasticsearch/OpenSearch ExperienceLLM Application Implementation

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Hard Skills

PythonSQLPostgreSQLTypeScriptNestJSElasticsearchClickHouseData ModellingWeb ScrapingDocument Parsing

Soft Skills

Product MindsetProposal WritingCollaboration

Tools & Technologies

RabbitMQKafkaPrefectMetabaseConfluenceDocker

Industry Keywords

Data GovernanceData QualityEvent-Driven ArchitectureHybrid SearchPublic Procurement

Tech Stack

Tools & technologies

AirflowCloudDockerElasticSearchJavaScriptKafkaNode.jsPostgresPythonRabbitMQSQLTypeScript

About the role

Key responsibilities & impact

Own Tendios data end to end, from scraping through customer-facing products and AI features
Propose and build data-driven features such as market intelligence, pricing benchmarks, contracting-body profiles, tender matching and alerting, and data-quality signals
Design and improve the retrieval layer behind Vera and Dynamic RAG, including document ingestion/conversion, chunking, embeddings, Qdrant indexing, Elasticsearch hybrid search and reranking
Use LLMs for structured extraction, classification, entity resolution and summarisation
Build evaluation sets and measure retrieval and answer quality
Provide clean, structured, documented data and tools for Vera and the Tendios MCP server
Define and measure data quality, retrieval quality, coverage, freshness, parsing accuracy and deduplication
Own and improve the collection pipeline, including Crawl Manager, Tenders Discovery, Collector, parsers and RabbitMQ consumers
Maintain consistent read models in Elasticsearch and Qdrant
Build the ClickHouse analytics layer, orchestrated with Prefect and exposed through Metabase
Replace manual Excel-based SaaS metrics reporting with a proper warehouse
Write production code in Python and TypeScript/Node.js within the NestJS Turborepo backend
Review code, set standards for data modelling and migrations, and document decisions in Confluence
Contribute to data governance and security, including ownership, retention, access and auditability
Report directly to the Head of Technology and collaborate with product, AI & Data, and backend squads

Requirements

What you’ll need

6+ years in software engineering, with at least 3 years focused on data-intensive systems
Strong Python and solid SQL
Deep, hands-on PostgreSQL experience, including modelling, performance and migrations at scale
Comfortable reading and writing TypeScript/NestJS
Experience building and running production data pipelines, including event-driven or queue-based architectures such as RabbitMQ, Kafka or similar
Experience with Elasticsearch/OpenSearch or ClickHouse
Hands-on understanding of LLM applications, including RAG, embeddings, vector search, chunking strategies, prompt design, tool calling, and retrieval/answer-quality evaluation
At least one LLM or RAG feature shipped to production
Product mindset and ability to write and defend proposals with product and business stakeholders
Fluent Spanish and English
Nice to have: web scraping and document parsing at scale, Qdrant or other vector databases, hybrid search and reranking, LLM observability/evaluation tooling, self-hosted open models on GPU infrastructure, Prefect/Airflow/dlt/dbt, large or legacy data migrations, public procurement/open data/regulated environments, Docker, and cloud or hybrid infrastructure experience

Benefits

Comp & perks

Fully remote from anywhere in Spain, or hybrid from the Barcelona office
Autonomous squads with a modern stack and pragmatic culture