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Top Data Engineer Jobs in Portugal
As a Principal Data Engineer at Material Bank, you will design scalable database systems for an eCommerce catalog, emphasizing BOM management and decentralized data ownership. Responsibilities include creating data models, developing ingestion pipelines, and ensuring data quality across multiple platforms. You will also lead the development of a self-serve data infrastructure for domain teams to autonomously create and manage data products.
As a Senior Data Engineer at Unity Ads, you will design and develop data pipelines and analytics products, collaborating with BI teams and stakeholders. You will ensure data quality and governance while leveraging cloud platforms and big data technologies. Proficient in Python and SQL, you will work across cross-functional teams to meet business objectives with scalable data solutions.
As a Lead Senior Software Engineer in the Data Platform team, you will design and implement optimized datasets, ensuring high quality and compliance. You will work collaboratively across teams to enhance data utilization, driving continuous improvement and innovation while addressing algorithmic and scaling challenges in a global context.
The Senior Informatica ETL Engineer will develop and maintain ETL solutions for a government client, focusing on data warehousing, data migration, and business intelligence projects. Key responsibilities include creating and managing ETL processes using Informatica PowerCenter, performing data analysis, and collaborating with users to enhance data delivery.
The Data Science Developer analyzes large datasets, develops machine learning algorithms, collaborates with medical professionals and software engineers, designs software tools for medical image processing, implements deep learning architectures, and ensures compliance with regulatory standards.
Develop and implement infrastructure for market data and trading, maintain market data feeds, and design large scale applications to reduce latency and improve performance.
The Data QA Engineer will oversee data quality, automate testing for data ingestion pipelines, write complex SQL queries, and design test cases using Python and SQL to ensure data integrity. The role also involves collaboration with analytic teams to enhance tools and resolve data issues.
Lead a team of data engineers in developing and managing an AI self-service portal and associated microservices. Collaborate with product owners and data analysts to enhance data platforms, optimize data collection, and build effective data pipelines. Guide best practices in software engineering and participate in the implementation of cloud-based solutions using Azure and Databricks.
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Design, implement, test, deploy, monitor, and support new and existing modules of the Data Platform for a high-tech home security company. Collaborate with external companies, internal teams, analysts, and data scientists to analyze data and ensure home security. Embrace a hybrid work model with flexibility between office and home.
The Senior Engineer, Data Scientist will analyze telemetry from memory products, develop machine learning models, and create data visualization reports. Responsibilities include statistical analysis, collaborating with teams, and communicating results to enhance product quality and reliability.
The Staff Data Engineer will lead the development of AI-driven data solutions, create real-time data pipelines, define architecture for Cloud Data Platform, and mentor staff on data engineering best practices, while collaborating with various teams to achieve enterprise data initiatives.
The Staff Software Engineer will design, develop, and maintain distributed software systems using C++, Golang, and Java on Linux. Responsibilities include identifying performance bottlenecks, conducting code reviews, mentoring junior engineers, collaborating with teams, and analyzing failures to resolve customer environment issues.
As a Senior Data Engineer, you will build and maintain data pipelines, working closely with various teams to support analytics needs. You'll participate in architectural decisions and promote best practices for data processing and modeling, influencing the company’s data systems and operations.
In this role, you will design and manage backend systems to support data integration and accessibility for Retool apps. Your responsibilities include building backend primitives, integrating APIs, and resolving customer issues related to data sources, ensuring smooth functionality and user experience across the platform.
The Associate Distinguished Engineer - Enterprise Data Architect will develop and implement a data management and analytics strategy, oversee data governance, manage data lifecycle activities, design data architecture, and evaluate technology solutions. The role requires collaboration with various departments and change management within the data function.
The Cloud Data Engineer III will architect, develop, and implement cloud data solutions. Responsibilities include optimizing data pipelines, implementing ETL processes, and working with big data technologies on AWS. The role involves collaborating with software engineers and data scientists to maintain and enhance existing data systems.
The Senior Data Science Engineer will develop data solutions, manage scalable data processing platforms, oversee algorithms for data acquisition and model improvement, and mentor junior engineers. Responsibilities include collaborating with teams, documenting solutions, and making informed decisions on services and applications.
The Lead Data Engineer will lead the development and implementation of data integration solutions. Responsibilities include managing a team, designing robust data pipelines, ensuring data quality, and optimizing workflows. This role involves collaboration with stakeholders and mentoring junior members in a fast-paced environment.
The Application Developer III will be responsible for working within the Surge Team BI – Data Engineering Team, utilizing technologies such as Apache Spark, AWS, and various programming languages to handle data engineering tasks. The role emphasizes cloud data processing and may include involvement with DevOps and containerization technologies.
Analytics Engineers at Axos Bank are responsible for designing and maintaining data infrastructure, developing data visualization tools, and collaborating with various stakeholders to create robust Data Analytics solutions. They perform data analysis, build automated data pipelines, and ensure code quality through reviews and testing activities.
The Sr Data Engineer will be responsible for expanding and optimizing the data pipeline architecture, collaborating with business leaders to create data assets, and participate in the design of the AWS-based data platform. The role demands extensive experience with SQL and AWS technologies, and involves building analytics tools for actionable business insights.
As a Data Support Engineer, you will generate and maintain report queries, provide user training on data interpretation, evaluate new technologies, and create documentation for systems. Additionally, you will develop automation scripts for workflows.
As a Senior Data Engineer at Cruise, you will architect & automate end-to-end data processing and management on Google Cloud Platform. Collaborate with XFN partners, build data pipelines, and mentor junior team members. Requirements include experience with Big Data Systems, Data Lakes/Warehouse/Lakehouse, ETL/ELT pipelines, Python/Java/C, Data Modeling, and SQL programming.
The Lead Data Engineer is responsible for developing and implementing data pipeline solutions, collaborating with stakeholders, designing large scale datasets, and mentoring junior developers. Key tasks include code reviews, technical documentation, and maintaining best practices for data structures.
As a Software Engineer, Data, you will build core data infrastructure for acquiring, preprocessing, cleaning, and labeling multimodal datasets for model training, enhancing the quality of the models. You'll be leading teams, managing projects, and working closely with data vendors to improve video understanding systems.
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