Top Data Engineer Jobs in Portugal

Lead Data Engineer responsible for designing, developing, testing, implementing, and supporting cloud-based data solutions. Collaborate across Agile teams on distributed microservices, streaming, and machine learning pipelines using Java/Scala/Python, RDBMS/NoSQL, and data warehousing (Redshift/Snowflake). Mentor engineers, perform unit tests, and deliver performant production systems.

Lead Data Engineer designs, builds, tests, and supports cloud-based data solutions. Collaborates with Agile teams on distributed, real-time, and full-stack systems using Java/Scala/Python, cloud data warehouses, big data and NoSQL technologies while mentoring peers.

Design, develop, test, implement, and support cloud-based data solutions. Lead and mentor engineering teams, build distributed and streaming data pipelines, optimize performance, and collaborate with product managers to deliver scalable data platforms.

Design, build, and operate enterprise data pipelines and Lakehouse data products on Azure. Lead migrations, implement medallion architectures, optimize Spark and distributed SQL workloads, enforce CI/CD and observability, and support production incident response while partnering with architects, data scientists, and stakeholders.

Build and maintain scalable pipelines to ingest, clean, and integrate large multimodal datasets. Own ingestion across APIs, files, cloud storage, and warehouses. Design linkage, entity resolution, deduplication, and schema harmonization. Implement data quality checks, validation, and documentation. Collaborate with engineering, research, and deployment teams to prepare integrated data for simulations and evaluate new data sources.

Design, build, and optimize secure data pipelines and stores for a Navy client. Convert tactical data formats, implement MIL-STD message handling, orchestrate ETL with Airflow/Kafka/Step Functions, support Cross-Domain Solutions, enable real-time indexing/querying, and present technical data flows to leadership.

Design and implement scalable data architecture and storage (cloud/on-prem), build and maintain ETL pipelines, enforce data governance and security, ensure data quality, evaluate technologies, collaborate with analysts and data scientists, and document data assets.

Build and maintain scalable ELT pipelines and analytics-ready datasets in SQL Server. Integrate SaaS/APIs, implement automated data validation and testing, develop star/snowflake data models, optimize performance, and support BI integration (Power BI) while partnering with stakeholders and documenting data systems.

Build, maintain, and troubleshoot data pipelines moving data into Snowflake. Write dbt models with tests/docs, backfill and validate data, investigate upstream data issues, run incident response for MSSQL/Snowflake/S3, and document processes.

Build and support high-performance data solutions, design and operate ETL pipelines and data warehouses, monitor production analytics tools, troubleshoot system issues, collaborate with product teams, and support TechOps for analytics infrastructure.

Senior consulting data engineer responsible for leading complex data engineering projects, coding robust solutions, designing complex data models, troubleshooting and optimizing data operations, mentoring engineers, interfacing with customers and cross-functional teams, and ensuring quality through testing, code reviews, and performance tuning to deliver on-time, on-budget solutions.

Build, scale, and monitor end-to-end data pipelines and infrastructure powering AI products; implement reporting solutions; optimize data models and queries; mentor teammates and support ML model productionization.

Build and maintain cloud-native data pipelines and architectures (warehouse, lakehouse, streaming) to support BI, analytics, ML, and GenAI. Collaborate with data scientists and stakeholders to produce AI-ready datasets, enforce data quality and governance, optimize performance and cost, and implement ingestion, ELT, and observability practices under mentorship.

Design, develop, maintain, and test complex enterprise software systems and cloud infrastructure. Implement solutions using COTS/GOTS, analyze system performance, troubleshoot issues, and collaborate with users and systems engineers. Emphasis on OpenStack-based cloud deployment, Linux and Python development, and IT operations support.

Design, build, and operate scalable Databricks-based data ingestion and transformation pipelines on AWS. Ensure governed, observable, production-grade lakehouse solutions with metadata, lineage, data quality, security controls, and CI/CD deployment to support analytics and regulatory compliance.

The Data Engineer will design, develop, and maintain scalable data systems, focusing on AWS and big data technologies to support data-driven decision-making and ensure data security.

Design, build, and operate Azure-based data pipelines (batch and near real-time) using Databricks, PySpark, Delta Lake, dbt and Snowflake. Ensure data quality, SLA ownership, CI/CD integration, and leverage AI-assisted tools (Claude/Copilot) to optimize engineering workflows in a telecom environment.

Design, build, and optimize data pipelines for massive datasets. Collaborate with stakeholders, implement CI/CD processes, and ensure data architecture scalability.

Lead design and hands-on delivery of a next-generation data platform and pipelines (batch, ELT, near-real-time) powering BI, experimentation, and ML. Own platform architecture, data modeling, governance, observability, and mentor engineers while modernizing legacy systems and driving AI-first data engineering practices across cross-functional teams.

Lead architecture and delivery of a cloud-native, petabyte-scale data platform: define technical roadmap, mentor engineers, build ETL/ELT pipelines, enable real-time streaming, implement Iceberg table format, optimize Snowflake/Redshift/Athena compute, and integrate observability with Splunk.

Design, build, and optimize scalable AWS-based data pipelines, data lakes, and warehouses. Migrate legacy systems, enforce data quality/security/governance, implement ETL/ELT and big-data solutions, adopt CI/CD and IaC, collaborate with stakeholders, and provide technical leadership and troubleshooting.

Lead end-to-end data engineering on GCP: design scalable data platforms and architectures (lake/lakehouse/warehouse), build and optimize BigQuery/Spark pipelines, ensure data quality/security, enable ML workflows with Data Science, mentor engineers, and own delivery and performance.

Design, build, modernize, and maintain operational and analytical data capabilities for Wealthscape Reporting, Analytics and Insights. Perform solution design, data analysis, ETL development, and production rollouts using Snowflake, AWS, cloud databases, and CI/CD pipelines. Collaborate across teams in a fast-paced financial services environment.

Design and build RAG-focused data pipelines for LLMs: ETL/ELT for structured and unstructured data, vector database architecture, embedding and chunking strategies, data cleaning/PII removal, metadata engineering, low-latency streaming, and evaluation/versioning to support autonomous agents.

Design, build, and maintain scalable data pipelines on AWS using EMR, Spark, and PySpark. Optimize EMR clusters and Spark jobs, implement ETL/ELT processes, ensure data quality, automate ingestion, and collaborate with data scientists and analysts. Document infrastructure, participate in code reviews, and monitor performance and costs.