Top Data Engineer Jobs in Portugal

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

Build and own data pipelines, models, quality checks, dashboards, and visualizations for manufacturing and test data. Partner with optical, manufacturing, and quality engineers to create reliable data solutions, improve pipeline performance and cost, and support engineering and leadership decisions. Establish software engineering practices for data systems, guide technical direction across distributed sites, and mentor other engineers.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Set up test, preproduction and developer environments on physical servers; act as SQL Server DBA including security auditing; develop Big Data solutions and programs; perform user acceptance and integration testing. Requires experience with DTS/SSIS/SSRS, T-SQL, C#, PowerShell, Hive/Hadoop, and Microsoft SQL Server 2000 certification.

Build and own the core data models and pipelines connecting product usage, accounts, revenue, billing, and customer health. Create trusted metrics, dashboards, and self-serve reporting. Partner with Product, Engineering, and GTM teams to improve data quality, design AI-enabled workflows and agents, and support leadership with accurate visibility into adoption, pipeline, retention, expansion, and revenue.

Apply systems engineering and data analysis to construct reliable data products, analytic models, and interactive dashboards (Qlik, Streamlit) using DoD analytics platforms (Advana). Curate and standardize force management data, translate operational needs into requirements, support lifecycle planning, integration, documentation, and stakeholder training for DoD decision support.

Design, develop, and maintain batch and streaming data pipelines and ETL for large unstructured datasets. Collaborate with developers, data scientists, and analysts to build data management systems, containerize and deploy services (Docker/Kubernetes), and implement CI/CD, DevOps, and monitoring on Linux/AWS infrastructure for intelligence community missions.

The Data Engineer will construct data infrastructure, develop machine learning workflows, maintain data pipelines, integrate software components, and collaborate across teams to enable data-driven decisions.

Build and own the companys core data foundation: design data models, pipelines, and trusted metrics connecting product usage, accounts, billing, and revenue. Partner with Product, Engineering, and GTM teams to improve data quality, create self-serve reporting, and automate workflows using AI. Balance foundational architecture with urgent business needs and enable consistent definitions and visibility across Sales, RevOps, Marketing, Finance, and Product.

The Founding Data Engineer will design and build scalable data systems, pipelines, and cloud infrastructure to support an AI recruiting platform, working closely with cross-functional teams and taking ownership of data solutions.

Lead end-to-end data integrations with utility customers: scope requirements, map and transform datasets, run and monitor pipelines, triage issues, and productize repeatable tooling to speed implementations.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

Design and maintain high-performance real-time dashboards, HMI/SCADA interfaces, streaming UIs, and post-processing tools for high-throughput sensor telemetry. Define visualization architecture, rendering standards, testing practices, and operational best practices. Collaborate with data platform, controls, and test automation teams while debugging and optimizing the full rendering-to-data stack in safety-critical, 24/7 environments.

Drive profitable revenue growth for industrial services serving data center customers. Develop market strategies, identify and close opportunities, negotiate pricing, manage assigned accounts, maintain sales records, support customer appointments, coordinate with sales and operations teams, and manage sales expenses. The role requires relationship building, customer support, and travel up to 50% while working remotely.

Drive profitable revenue growth for data center and industrial water services across assigned accounts. Develop market strategies, identify and negotiate opportunities, close sales, manage customer relationships, analyze requirements, coordinate with sales and operations teams, document activity, support major job scopes, and control sales expenses. The role is remote and requires travel up to 50%.

Responsible for profitable revenue growth across assigned accounts and territories. Develops market strategies, identifies and negotiates sales opportunities, analyzes customer requirements, manages account revenue, builds customer relationships, documents sales activity, supports major job scopes, coordinates with sales and operations teams, and controls sales expenses. The role focuses on industrial services for data centers and requires up to 50% travel while working remotely.

Drives profitable revenue growth for data center and industrial services accounts. Develops market strategies, identifies and negotiates sales opportunities, analyzes customer requirements, maintains account information, builds customer relationships, supports major job scopes, collaborates with sales and operations teams, coordinates customer support, and manages sales expenses. Travel up to 50% is required, with remote work available.

Owns profitable revenue growth for data center and industrial water services accounts. Develops market strategies, identifies and negotiates opportunities, analyzes customer requirements, manages pricing and revenue responsibilities, maintains sales records, supports customer appointments, collaborates with sales and operations teams, and builds long-term customer relationships. The role requires up to 50% travel and may be performed remotely.

Drive profitable revenue growth for industrial services targeting data center customers. Develop market strategies, identify and negotiate opportunities, manage assigned accounts, build customer relationships, analyze requirements and pricing, document sales activity, coordinate with sales and operations teams, support major job scopes, and manage sales expenses. The role requires relevant sales experience, preferably serving data centers or general contractors, and travel up to 50% while working remotely.

Build and shape an agent-orchestration platform using frontier LLMs. Transform heterogeneous enterprise program data into structured, queryable knowledge, develop reliable and observable backend services, and own features from design through production. Collaborate with product management and customers, make prioritization decisions, review code, write tests, and support production systems. The role requires strong Python backend skills, LLM production experience, cloud expertise, and comfort solving ambiguous startup problems.

Build, operate, and enhance Banc of California’s Azure- and Snowflake-based data platform. Develop batch, CDC, and streaming ingestion pipelines; optimize Snowflake performance; support dbt workloads; implement CI/CD, DataOps, monitoring, automation, and disaster recovery. Provide Tier 2 production support and administer tools including Power BI, Purview, and Alteryx. Collaborate with data engineering, architecture, BI, and business teams to deliver secure, reliable, governed data solutions.

Own the architecture, technical direction, reliability, and evolution of a shared cloud data platform. Lead hands-on development of streaming and batch pipelines using infrastructure-as-code, build governed analytical data products, and establish data contracts, quality, security, lineage, and observability standards. Serve as the final technical escalation point, mentor engineers, lead design and code reviews, promote responsible AI-assisted coding, respond to incidents, and communicate technical tradeoffs across stakeholders.

Own the architecture and evolution of Osmo’s canonical data platform, including data models, schemas, migrations, replication, APIs, integrations, access control, validation, concurrency, and auditability. Lead consistency across distributed systems under retries and partial failures, establish data modeling standards, partner with scientific and technical experts, and improve team capability through durable engineering practices and mentorship.

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.

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.