Senior GCP Data Engineer | BPCE-SI at Natixis in Portugal

, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

25 Jun, 26

Salary

0.0

Posted On

27 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GCP, BigQuery, Cloud Composer, Apache Airflow, SQL, Python, Data Migration, ETL/ELT, SQL Server, Schema Design, Data Pipelines, Automation, Code Reviews, Monitoring, Data Quality, Problem-Solving

Industry

IT Services and IT Consulting

Description

Company 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. As part of Groupe BPCE’s international division, Natixis in Portugal designs and delivers solutions for its two core areas — Corporate & Investment Banking and Asset & Wealth Management — as well as transversal services that support all entities across the Group. With more than 3,000 employees representing 46 nationalities, the teams work across Information Technology, Banking Support Activities, and Compliance, in an integrated, inclusive, and cross-functional way, supporting all business lines and platforms of the Group. 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. Job Description Natixis in Portugal is currently seeking a Senior GCP Data Engineer to join its BPCE SI (BPCE Solutions Informatiques) team, within the IT (Information Technologies) department, to work in a hybrid model in the Porto or Lisbon office. Responsibilities Data and Database Migration: Actively participate in the design and execution of the data and ETL process migration strategy from SQL Server to GCP. Develop and optimize scripts and pipelines for efficiently transferring and transforming data into BigQuery. Design and Development of Data Pipelines on GCP: Design, develop, and maintain robust and high-performing ETL/ELT pipelines on GCP, replacing or rebuilding existing flows. Orchestrate and schedule these pipelines using Google Cloud Composer (or Apache Airflow) to ensure reliable migration and operationalization. Database Management and Optimization on GCP: Develop and optimize complex SQL queries for BigQuery, taking into account the specificities of migrating from SQL Server to BigQuery (e.g., optimizing partitioning, clustering). Contribute to the design and implementation of optimized data schemas for BigQuery, adapted to new cloud architectures. Development and Automation: Use Python to develop scripts for automating migration tasks, data transformation, and integration with other GCP services. Implement processes to ensure data quality and integrity during and after migration. Collaboration and Support: Collaborate closely with current teams (SQL Server administrators, analysts) to understand the existing environment and facilitate the transition. Exchange with end-users (business lines, data scientists) to understand their needs and ensure the new platform meets their expectations. Participate in code reviews, development best practices, and testing strategies for the new platform. Ensure monitoring, debugging, and incident resolution related to data pipelines during the transition phase and upon production deployment. Technological Watch and Optimization: Stay informed about best practices for migration and the latest developments on Google Cloud Platform. Propose improvements and optimizations for the new Data platform on GCP. Qualifications Mastery of Google Cloud Platform (GCP): BigQuery: Significant experience in schema design, writing complex queries (SQL), performance optimization, and cost management in a cloud context. Cloud Composer / Apache Airflow: Solid experience in creating, scheduling, monitoring, and debugging DAGs to orchestrate data flows, particularly for migration and integration processes. SQL: Excellent mastery of the SQL language. Experience with SQL Server is a plus, but more importantly, the ability to adapt and optimize SQL for BigQuery. Python: In-depth mastery of the Python language for developing scripts (migration, automation, data transformation) and interacting with GCP APIs. Data Migration: Experience or strong understanding of the challenges and methodologies for migrating databases from an on-premise environment (SQL Server) to a cloud environment (GCP). Analytical and Problem-Solving Skills: Ability to analyze existing systems (SQL Server), understand business needs, design solutions on GCP, and resolve complex problems related to migration and pipeline operation. Personal Qualities: Autonomy, rigor, organizational skills, teamwork ability, technical curiosity, and the capacity to adapt to a new environment. Additional Skills (Good to Have): Direct knowledge of SQL Server (architecture, T-SQL, basic administration). Experience with other GCP services relevant to data migration and integration (Storage, Dataflow, etc.). Knowledge of GCP-specific migration tools and strategies (e.g., Database Migration Service). Experience with data visualization tools (Power BI). Understanding of Data Warehousing concepts and data modeling (Data Vault). Experience with code versioning. Good communication skills in English are required (+B2 level required). We will only consider CVs in English. Additional Information Our workplace reflects the vibrant spirit of our locations, with initiatives such as a Green Transportation Budget, electric bikes and a flexible Hybrid Work Policy. We promote wellbeing through the Honolulu Wellness Club, a Prayer Room, a Lactation Room, and themed Villages that inspire creativity and collaboration. Through our ESG and DEI strategies, we are committed to being inclusive, caring, and fair, ensuring every voice is heard and valued.

Responsibilities

The Senior GCP Data Engineer will be responsible for designing and executing the data and ETL process migration strategy from SQL Server to GCP, focusing on developing and optimizing pipelines for BigQuery. This includes orchestrating flows using Cloud Composer/Airflow and ensuring data quality and integrity during and after the transition.