Top Data Engineer Jobs in Barcelona

Maintain and extend distributed ETL pipelines and BigQuery datasets, build and operate REST microservices, optimize analytical queries, operate AI-powered tooling, and ensure backward compatibility across authentication flows.

Lead the design and delivery of scalable data platforms and pipelines supporting analytics, products, and business decisions. Set technical direction across data architecture, storage, transformation, and serving layers while improving reliability, quality, and maintainability. Mentor engineers, conduct code reviews, solve complex technical problems, and influence cross-functional stakeholders. The role requires hands-on engineering across cloud infrastructure, orchestration, APIs, databases, software delivery, and large-scale data environments.

As the Data Engineer, you will design and maintain data pipelines, scale data infrastructure, ensure data quality, and collaborate with analysts to enhance decision-making capabilities.

Leads electrical design for hyperscale and mission-critical data centers across Europe. Responsibilities include managing HV/MV/LV systems, substations, utilities, consultants, permitting, project delivery, construction support, commissioning, and integrated systems testing. The role provides client-side technical leadership, reviews designs and project documents, coordinates multidisciplinary teams, manages risks and milestones, and ensures compliance with standards and operational requirements.

Develop and maintain high-volume data processing pipelines using cloud and distributed-data technologies. Build jobs and libraries supporting data scientists and analysts, while implementing monitoring, alerting, quality checks, testing, and documentation. Contribute to data platform architecture and collaborate with cross-functional teams. The role requires expertise in SQL, data modeling, workflow orchestration, Python, ETL/ELT design, Spark, and AWS.

Develop high-volume distributed data processing jobs using Redshift, Athena, Iceberg, Spark, and Airflow. Collaborate with data scientists, analysts, and product managers to turn methodologies into products, improve system performance, and support data workflows. Mentor junior engineers on architecture and best practices. The role requires strong Python programming, SQL, database, data modeling, and modern lakehouse expertise, with AWS and streaming experience preferred.

Develop, operate, and optimize a multi-tenant Azure data platform using Data Factory, ADLS Gen2, Databricks, and Synapse Analytics. Build scalable PySpark and Spark ETL/ELT pipelines, maintain data infrastructure, implement CI/CD automation, optimize cost and performance, and support data governance, security, modeling, and reporting. Collaborate with BI and data teams across development, test, and production environments.

Build and own end-to-end data foundations, including ingestion pipelines, dbt models, data marts, semantic layers, and AI-ready datasets. Integrate fragmented marketing, advertising, ecommerce, analytics, and CRM data across a multi-tenant Snowflake environment. Manage platform API changes, data quality, restatements, performance, and client-specific modeling. Collaborate with product, engineering, AI, BI, and client teams while using AI coding agents to accelerate reliable production development.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

The Renewables Measurement & Data Engineer will validate renewable measurement data, support on-site measurements, troubleshoot systems, and analyze resource potential and asset performance.

Lead data engineering initiatives across large-scale e-commerce datasets. Own data models, transformation architecture, analytics projects, client data products, internal dashboards, documentation, and technical roadmap delivery. Collaborate with technical and business stakeholders, mentor teammates, and translate business needs into scalable data solutions using SQL, BigQuery, Google Cloud, ETL/ELT tools, and visualization platforms.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

Freelance Senior Data Solution Engineer responsible for delivering approximately two custom client data projects monthly. Duties include qualifying requirements, analyzing large datasets with Python and SQL, building dashboards and predictive models, developing business recommendations, presenting findings to clients, documenting projects, and sharing insights with Product. The role requires fluent Spanish and English, freelance status, and availability for a full-time four-to-five-month mission based in Barcelona or Madrid.

Design and scale cloud-native data platforms, including batch and streaming pipelines, data replication, workflow orchestration, and infrastructure automation. Build Python and SQL transformations, manage Kafka-based real-time systems, establish data governance and quality controls, and develop performant data models for reporting and business intelligence. Partner with business stakeholders to translate requirements into reliable, scalable data solutions.

Design and build durable, distributed data-streaming infrastructure that decouples process data from Camunda’s live execution engine. Develop customer-facing integrations such as Kafka connectivity, support analytics data consumption at scale, and make architecture decisions around consistency, durability, and storage. Participate in production support and on-call rotations while collaborating with Product, Data Layer, Distributed Systems, QA, SRE, and Support teams. Lead ambiguous, cross-functional engineering initiatives from design through delivery.

Build and maintain Camunda 8 backend data-layer services spanning relational databases and Elasticsearch/OpenSearch. Design scalable storage, query, retention, and streaming systems; improve performance, indexing, and production tooling. Lead engineering initiatives from solution design through delivery, collaborate across teams, provide L3 support, and participate in on-call rotations. Investigate production data issues and contribute to schema evolution, workflow automation, and CI improvements.

Design, implement, and test cloud-based server-side software in Python. Optimize code performance, maintain unit and integration tests, and work with AWS, Docker, DevOps, and CI/CD tools. Preferred experience includes reverse engineering public APIs, PostgreSQL, Django ORM and DRF, network protocols, and web or mobile technologies.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

Design, build, and operate reliable, scalable backend services, APIs, and platform components. Lead complex feature development from planning through release, improve service performance, monitoring, alerting, observability, and operational readiness, and collaborate with engineering, product, and QA teams. Serve as a technical contributor for debugging and architecture decisions while mentoring junior engineers and advancing engineering standards.

The Data Engineer will build scalable infrastructure for data analysis, ensuring high performance and compliance with data protection standards 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.

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

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

Build and improve data infrastructure and pipelines, integrate sources, develop analytical data models and reporting, perform ad-hoc business analyses and scenario simulations, and enable data-driven decision-making across teams.

Build and evolve a cloud-based data platform (Databricks/AWS) to support analytics and AI. Design scalable data pipelines, enable ML/AI in production, enforce governance/observability, define engineering standards, and mentor the data team while collaborating with product, engineering, and business stakeholders.