Senior Data Engineer
Porto, Porto, Portugal
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Natixis in Portugal
Welcome to the common website of Natixis CIB and Natixis IMCompany Description
Natixis in Portugal is a Centre of Expertise whose mission is to transform traditional banking by developing innovative solutions for the business, operations and work culture of Groupe BPCE worldwide.
Natixis in Portugal is part of the Global Financial Services division, where it applies technology for the development of financial expertise in its two global business lines – Corporate & Investment Banking and Asset & Wealth Management – and, transversally, for the entities of Groupe BPCE.
The Centre of Expertise, based in Porto, currently has more than 2,400 employees from over 30 nationalities, organised in three main departments: Information Technology, Banking Support Activities and Compliance. These teams work in an integrated, inclusive and transversal way, supporting and creating value for all the business lines and platforms of the group. The project in Porto is one of the biggest investments in Human Resources ever made by Groupe BPCE worldwide.
A disruptive mindset and a culture of proximity and agility identify Natixis in Portugal Team and reflect the company's mission to transform traditional banking at a global scale: a perfect match in the Portuguese dynamics and entrepreneurial ecosystem.
In 2024, Top Employers Institute has awarded Natixis in Portugal the Top Employer Portugal accreditation for the second time. This certification recognizes excellence in people practices, following the example of our head office, in France, who was certified Top Employer France for the eight year in a row.
Job Description
We are looking for a Senior Data Engineer to join the IT Payments Data Team. The project is being developed by a team that is present in Paris and Porto and is mainly responsible for the evolution and support of the product. Designing, developing, and implementing scalable and efficient data solutions for the payments domain.
Main tasks:
- Participate as a technical referent in developing code for processing and analyzing large amounts of data (e.g. unstructured tracking data, large full-text data sets, graph data, etc.).
- Design and implement highly scalable batch or real-time data processing workflows/components and products that make smart use of data to provide data-driven functionality (e.g. search services, recommender services, classification services, etc.), leveraging machine learning, Big Data technology, and distributed systems.
- Build, monitor and operate services delivery within the Natixis infrastructure, while enhancing data quality/utility and automating processes.
- Deploy solutions on cloud technologies, mainly GCP (Google Cloud Platform)
- Work in a cross-functional team and collaborate closely with Data Scientists and Analysts to support the (technical) design, implementation and evaluation of new algorithms, machine learning models and other data-driven features and services.
- Guide and support team members through technical issues and challenges related to data engineering and the uses tech stack.
Qualifications
- Degree in Information Technology or Computer Engineering, Computer Science or a related field.
- Between 3 to 9 years of experience in designing and implementing scalable software and data-driven services using Big Data technologies, data storages (e.g. relational databases, key-value stores), data warehouses, data lakes, data lakehouses and related data processing technologies, as well as programming languages such as Spark / Python / Java / Scala (for real-time and batch processing).
- Experience in building and optimizing data pipelines that process large datasets using Spark and cloud computing environment.
- Experience with working on cloud environments especially with data related services, for example BigQuery, BigTable, Dataproc, GCS, Composer, GKE on Google Cloud Platform and low-code/no-code (e.g YAML) approaches for ETL tools.
- Experience in Business Intelligence and SQL utilization on analyzing large datasets.
- Experience with workflow management platforms (like Airflow) and collaborative platforms (like Jupyter)
- Some experience in the domain of information retrieval, information extraction or machine learning/AI concepts and technologies is a plus.
- Good knowledge of Agile methodologies (SAFe / Scrum).
- In-depth understanding of software development processes, CI/CD methodologies, Devops overview and quality assurance practices. (e.g. XLRelease/XLDeploy, Terraform, Jenkins, GIT, Bitbucket, etc)
- Microsoft Azure and PowerBI is a plus.
- Familiarity with AI concepts and technologies is a plus but not a primary focus of the role.
Additional Information
#MuchMoreThanJustAJob
Early morning. Campo 24 de Agosto. In 4 minutes, you are clocking in at the office. After grabbing a cup of coffee and fresh fruit, pick up your laptop and choose your spot for the day. It's going to be a busy one: French class before lunch and, just after, quick medical appointment at Natixis doctor's office.
Lunch break. Outside in the big terrace (look at your crops at the Urban Garden; ready to harvest!) or, if you feel like stretching your legs, walk downtown to grab lunch.
Back inside. Quick sprint review (working together anywhere means virtual happy birthday to that colleague in Paris that just turned 35). The afternoon went flying (tasks, reports, calls, some jokes with your teammates). End it on a high note: just one PlayStation game or the final match for that ping-pong tournament.
Tomorrow, you complete that certified technical training and the day after, you will work from home, taking advantage to finally do that online course on Udemy. Once you are done with your tasks for the day, you can visit the office for a board games session or show up at the rehearsal of one of Natixis bands. If that is too steady for you, meet your colleagues to surf some waves or join them in a football match.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow Azure Banking Big Data BigQuery Bigtable Bitbucket Business Intelligence CI/CD Classification Computer Science Data pipelines Dataproc Data quality DevOps Distributed Systems Engineering ETL GCP Git Google Cloud Java Jenkins Jupyter Machine Learning ML models Pipelines Power BI Python RDBMS Scala Scrum Spark SQL Terraform
Perks/benefits: Gear Team events
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