Top Data Engineer Jobs in Lisbon

Design, build and maintain enterprise ETL/ELT pipelines and data solutions on a Microsoft-centric cloud platform. Lead data refactoring and integration projects, enforce data governance and quality, document architectures, and collaborate with Dynamics 365, Power Platform and cross-functional teams to deliver reliable, performant data pipelines.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

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, build, deploy, and maintain scalable batch and streaming data pipelines and lakehouse architectures. Monitor and optimize dataflows, partner with engineering teams to solve data challenges, and ensure governance and high-performance data solutions across the company.

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, build, and maintain scalable ETL/ELT pipelines and data warehouses for ad-tech analytics. Ingest and normalize SSP/DSP/GAM data, transform raw logs into analytics-ready models, implement data quality checks, and support BI teams to power campaign and revenue insights while ensuring GDPR/CCPA compliance.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

The Tableau Developer will design, build, and maintain Tableau dashboards, optimizing performance and ensuring data accuracy while collaborating with stakeholders.

As a Senior Data Engineer, you will ensure the stability and performance of the Data Science Framework. Responsibilities include re-architecting big data components, analyzing workload patterns, and collaborating with product engineers and data scientists to improve system reliability and developer experience.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

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.

Lead hands-on data engineering: design Postgres CDC -> Kafka -> Snowflake pipelines, own ingestion/orchestration/transformation/quality tooling, implement CDC ingestion, build streaming near-real-time pipelines and data quality controls, define data contracts and tenant separation, deliver external client-facing data products, and grow a small data engineering team.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

The Data Engineer will construct data pipelines, manage ETL processes, optimize SQL queries, and ensure data integrity, utilizing various tools such as Airflow, Python, and SQL.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.