Top Data Engineer Jobs in Lisbon

Design, build, and maintain Snowflake and dbt pipelines for the US revenue data chain (Billing → ARR → Deferred Revenue → Rev Rec → Close Pack). Deliver tested, documented ingestion and transformation models, ensure pipeline reliability during financial close (on-call), set data quality and governance standards, enable AI and finance consumers, and extend models to OPEX/COGS/commissions as scope grows.

The Senior Data Engineer will develop and maintain data pipelines, support data analysis, ensure architecture meets business needs, and communicate with stakeholders.

The Software Engineer will support data collection for model training, manage ingestion pipelines on GCP, and collaborate with data scientists to enhance dataset quality and scale.

Own the finance data domain by developing financial data products and models, integrating and improving data quality, monitoring freshness and completeness, and resolving reconciliation issues. Build reports, alerts, automations, and LLM agents using Python, SQL, Snowflake, Airflow, and dbt. Communicate data issues clearly to Finance leadership and ensure financial reporting and planning data remains accurate and reliable.

The Staff Engineer will define architecture, lead data pipeline design, ensure platform reliability, and mentor engineers, driving data initiatives and technical standards.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Maintain and expand a high-scale data platform: build and run data pipelines, implement DataOps, collaborate with analytics teams, ensure data quality and security, and design enterprise data models.

Lead migration from BigQuery to a Databricks Lakehouse: design scalable Delta Lake medallion architectures, build and optimize PySpark data pipelines, implement governance with Unity Catalog, support CI/CD, troubleshoot SQL/Spark workloads, collaborate with cross-functional teams, and contribute to platform modernization and reliability.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Build and maintain cloud and on-prem data pipelines, monitor and resolve batch failures, engage stakeholders to translate business needs into data solutions, deliver projects end-to-end, coach junior teammates, and define best practices for the UK data platform.

Design and build scalable real-time and batch data pipelines for programmatic advertising data. Ingest, normalize, and model bid streams, impressions, revenue, and partner performance data from SSPs, DSPs, ad servers, and reporting APIs. Maintain data warehouses and lakes, implement quality monitoring and anomaly detection, support BI teams, and ensure GDPR and CCPA compliance. The role involves high-volume, low-latency systems and collaboration on yield optimization and auction analytics.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Design, develop, and optimize data solutions to support BI and analytics. Build ETL/data integration processes, schedule and automate jobs, maintain Teradata data warehousing, and apply CI/CD/DevOps practices. Collaborate with stakeholders, document work, and ensure high quality and reliability in a UNIX environment.

Operate, monitor, and support Hadoop-based data lake platforms; provide L3 incident response, troubleshooting, performance tuning, security management (Kerberos, Ranger/Sentry, TLS), capacity and replication management, automation for monitoring, and collaborate to onboard workloads and maintain documentation.

Design, build, and optimize Alteryx workflows and data transformation pipelines. Integrate relational databases using SQL, support analytics and BI initiatives, and improve complex ETL processes to deliver actionable analytics solutions.

Design, build, and operate Feedzai's cloud-native data platform and large-scale distributed data processing systems. Develop self-service tooling, maintain and scale mission-critical pipelines on Kubernetes, review and optimize pipelines, collaborate with product and data science teams, mentor engineers, lead small teams, and apply AI tools to streamline workflows.

Senior analytics engineer responsible for data governance, analytical modeling, and platform efficiency in BigQuery/GCP. Build reusable, trusted datasets, define semantic layers and analytics architecture, optimize performance and cost, establish data contracts and standards, and partner cross-functionally to support monetization, LiveOps, payments, and AI/ML workflows.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Build and modernize cloud-first, data-focused backend microservices using Java and Spring Boot. Design scalable APIs, optimize SQL and stored procedures, integrate with cloud and legacy systems, deploy to Kubernetes with Helm, collaborate with data teams, and ensure testing, CI/CD, and production reliability.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.