Top Data Engineer Jobs in Barcelona

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Design and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

The Principal Customer Data Platform Engineer will manage the customer data architecture, focusing on tracking, identity resolution, compliance, and data governance for Airalo. They'll collaborate with cross-functional teams to ensure systematic data flow, integrity, and compliance across various platforms and lead architectural decisions.

The Senior Data Engineer will lead the design and evolution of scalable data architectures, mentor team members, build data pipelines, and integrate Generative AI into workflows.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Design, develop, and maintain scalable backend services and APIs; manage and serve ML models in production (MLOps); ensure performance, security, and high availability; optimize databases; implement authentication/authorization; write tests; monitor with observability tools; collaborate across teams and maintain technical documentation.

The Senior Data Platform Engineer will lead project delivery for data infrastructure, manage near real-time services, and collaborate across teams while contributing to AI and data governance frameworks.

The Senior Data Engineer will manage data infrastructure, optimize data workflows, and collaborate with teams for seamless data accessibility and machine learning support.

As a Senior Data Engineer, you'll design and implement data solutions, develop AWS infrastructure, optimize data management, and standardize DataOps practices.

Design and build a greenfield, high-scale backend data platform: own architecture and stack, implement low-latency data pipelines and APIs, collaborate with Growth and Product, and grow a team.

The Senior Data Engineer develops data solutions, builds scalable data pipelines, and fosters best practices while collaborating within a multidisciplinary team.

Own and evolve the GDPR Orchestrator platform: design and operate its core engine, safety mechanisms, and observability. Build docs, templates, and self-serve tooling so product areas manage data rules. Coordinate cross-area requirements with legal, security, and data teams. Improve platform developer experience, safety, and scale integrations across data stores and third-party systems.

The Lead Software Engineer will develop AI-powered software solutions, design backend systems, and collaborate with cross-functional teams to enhance AI capabilities.

Design, build, and own Preply's data lake and end-to-end batch and streaming ingestion pipelines. Implement data contracts, quality checks, enrichment logic, observability, governance, and self-service tooling. Collaborate cross-functionally to ensure production-ready, reliable, and discoverable datasets for analytics, ML, and product.

The Senior Data Engineer will design, build, and maintain data pipelines, ensuring data quality, governance, and performance optimization while collaborating with cross-functional teams.

As a Lead Data Engineer, you will design, build, and maintain scalable data platforms, assess data landscapes, and collaborate with stakeholders to translate requirements into robust data solutions.

Investigate marketing tracking discrepancies, trace and fix end-to-end data pipelines (especially GA4/Salesforce and gclid issues), improve revenue attribution and reporting, and partner with marketing, engineering, and sales to implement reliable tracking and reporting solutions.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

As a Senior Data Engineer, you will deliver complex projects, manage customer relationships, and mentor junior engineers while using Databricks and various cloud platforms.

Design and maintain data infrastructure and tooling, develop scalable data pipelines, ensure data quality and security, and collaborate with other teams to enable insights.

The Senior Development Engineer/Mathematician/Data Analyst will develop algorithms, create statistical models, and implement biometric methods to enhance diagnostic accuracy and support product approvals.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

Design and implement end-to-end data architecture (Postgres CDC -> Kafka -> Snowflake). Own ingestion, orchestration, transformation, streaming pipelines, and data quality. Define data contracts, tenant separation, replay/reload, and external delivery. Start hands-on and grow a small data engineering team with a 3/6/12-month roadmap.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.