Top Data Engineer Jobs in Portugal

As an FP&A Data Engineer, you will manage data pipelines, develop financial models, and automate reporting to assist management and teams in making data-driven decisions.

Design, build, and maintain scalable relational databases, data warehouses, and integration workflows. Optimize SQL performance, ensure data integrity/security, support reporting/analytics, and collaborate with business stakeholders for timely, compliant reporting and continuity efforts.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

As a Market Data Support Engineer, you'll design, implement, and support Linux systems, manage infrastructure changes, and maintain co-location market data infrastructures.

Hands-on technical lead for global Azure-based data analytics environments. Own escalation support for complex incidents, performance/scalability troubleshooting on large datasets and pipelines, guide support analysts, and partner with engineering to drive durable fixes across Databricks, SQL Server/DWH, and Azure data services.

Build and maintain scalable cloud-native ETL/ELT pipelines and data platforms to support analytics and ML. Implement IaC and CI/CD, enable MLOps, ensure data quality, monitoring, and collaborate with data scientists and product teams to deploy production AI services.

Design, develop, and monitor large-scale data pipelines and cloud-native data applications; collaborate with consulting teams and clients; apply best practices (TDD, CI/CD); build and operationalize ML-ready data platforms; produce documentation and runbooks; mentor junior engineers and contribute to proposals and analytics assets.

Lead customer integrations by building warehouse-native or managed ClickHouse pipelines, construct semantic metadata layers, canonicalize source data into unified growth models, and act as the technical lead for enterprise deployments while partnering with AI discovery agents to accelerate onboarding and mapping.

Remote multi-role data position covering Data Analyst, Data Engineer, and Data Scientist duties: analyze and visualize data, write complex SQL, build dashboards, perform A/B testing and segmentation; design scalable ETL/ELT pipelines, maintain data lakes/warehouses, enforce data quality and monitoring; and develop machine learning models and predictive analytics to drive business decisions while collaborating across teams.

Design and maintain ELT/ETL pipelines and cloud data warehouse models, build Power BI reports, apply AI tools to accelerate data workflows, and partner with business stakeholders to deliver reliable analytics and data governance.

The role involves building data pipelines, processing structured and unstructured data, and collaborating with a multidisciplinary team on technology solutions for clients in various sectors.

As a Data Engineer, you will design, build, and maintain scalable data platforms, working on mission-driven projects that analyze big data to derive insights. You will collaborate with multi-disciplinary teams in a fast-paced environment.

Build and maintain centralized pricing data infrastructure, scalable workflows, and data pipelines; integrate AI capabilities; deliver pricing tools, reporting, and governance to support data-driven pricing and budgeting across the firm.

Build and scale core data infrastructure and foundational datasets. Design, develop, and maintain scalable data pipelines for analytics, ML, experimentation, and product use cases. Implement data quality, audits, alerting, and anomaly detection. Partner with product, engineering, and business stakeholders and help establish long-term, scalable data architecture and tooling.

Build production-ready analytics and ETL solutions to support Internal Audit. Perform data modeling, engineering, governance, entitlement management, and write analysis code to improve audit sampling, detect control gaps, and automate audit processes.

Design, build, and operate enterprise-scale data ingestion and transformation pipelines in Microsoft Fabric/Azure. Lead legacy migrations, implement data quality, monitoring, and governance, optimize pipelines for performance and cost, onboard data domains, and prepare high-quality data assets for Power BI and downstream analytics while documenting standards and collaborating with cross-functional teams.

Build and maintain Snowflake-based data warehouse and lakehouse components. Develop and optimize dbt models and SQL transformations, implement and monitor data pipelines, support CI/CD and orchestration workflows, contribute to cloud and Snowflake configuration, improve data quality and reliability, troubleshoot issues, and document data models and runbooks while collaborating with platform and analytics teams.

Lead Data Engineer at Schonfeld focuses on developing and advancing talent while leveraging proprietary technology for investment strategies, fostering a collaborative work environment.

Lead design and build of scalable batch and streaming data pipelines for multimodal and spatial AI. Enable dataset curation, versioning, lineage, and data quality for research-to-production ML workflows. Partner with researchers and architects, run proofs‑of‑concept, optimize cost and performance, and mentor engineers to maintain observable, reproducible AI data systems.

Design, build, and support data pipelines and workflows to clean, integrate, extract, analyze and deliver structured and unstructured data. Implement and customize TRSS client solutions and POCs, provide solution architecture input, automate internal processes (including RPA), and support customer-facing deployments. Collaborate with product, software engineering, data science, and business teams to meet unique client requirements and integrate TRSS content into client applications.

Lead design, development, and optimization of Snowflake-based data platforms and scalable ELT/ETL pipelines. Build dimensional models, data marts, and curated analytical datasets; implement Snowpark, stored procedures, streams, tasks; enforce data quality, lineage, governance, and security; automate orchestration with Airflow/Azure Data Factory/AWS Glue; support finance, risk, compliance, and regulatory reporting; mentor junior engineers.

Lead design and delivery of API and data engineering solutions: build end-to-end data pipelines, develop ontologies and schemas, ensure data quality and governance, integrate systems (including cloud/GCP), enable AI capabilities, enforce security/compliance, and mentor/lead technical teams within an Agile consulting environment.

Design, build, and maintain data pipelines and Azure data warehouse infrastructure. Ensure data quality, governance, performance tuning, automation, and provide BI insights using Power BI or QlikSense.

Intern will explore and clean unfamiliar datasets, write code to ingest, transform, and monitor data quality using Python, SQL, and OCaml, work with structured and unstructured data, complete two owned projects, and be mentored by full-time Data Engineers.

The Data Engineer will maintain and optimize data pipelines, manage infrastructure, support ML workflows, and collaborate with teams on data products.