Data Engineer (Data Ops Focus)

Your opportunity with a fast-growing, innovative team

Become part of radicant, a dynamic start-up dedicated to shaping the future of digital banking. We're expanding quickly, bringing personalised financial services closer to people through advanced technology and strategic partnerships. Our goal is to support customers in achieving their financial objectives in a convenient, accessible way—24/7.

 If you have a digital mindset and are excited about joining a purpose-driven team, radicant offers the chance to make a meaningful contribution while advancing your career in a fast-paced, collaborative environment.
 
 Join our Data Engineering Team – As a Data Engineer with a Data Ops focus, you will work closely with other teams to ensure seamless data integration, transformation, and availability for analytics, ensuring our cloud-native data infrastructure is efficient, reliable, and scalable.

Your Impact

Data Pipeline & Real-Time Processing

• Design, develop, and maintain real-time data pipelines using Apache Kafka, Pub-Sub, and other messaging brokers for seamless data streaming
• Build scalable, reliable data pipelines that process both real-time and batch data efficiently
• Troubleshoot and optimize data workflows to ensure high performance and reliability

Database Management & Optimization

• Manage, query, and optimize databases (PostgreSQL, SQL Server) for high performance and scalability
• Use strong SQL skills for data transformation, analysis, and performance tuning

Cloud Data Services & Data Ops

• Work with Google Cloud Platform (GCP) services such as Cloud Composer (Apache Airflow), Dataflow, BigQuery, and Cloud Run to build and maintain cloud-native data pipelines
• Implement CI/CD practices for data pipeline deployments, ensuring efficient automation and reliable workflows

Data Modeling & Transformation

• Utilize dbt for transforming, testing, and documenting data models, ensuring data accuracy and consistency across platforms
• Apply data modeling principles to design scalable, maintainable data warehouses

Stakeholder Collaboration & Agile Execution

• Collaborate with cross-functional teams to integrate data from various sources into the data pipeline
• Contribute to Agile workflows and communicate progress effectively to ensure timely delivery of high-impact data solutions

What makes you a great fit

• Educational Background: MSc or BSc in Data Engineering, Computer Science, or a related field
• Professional Experience: 3+ years in data engineering, with a strong focus on real-time data processing and cloud environments
• Mindset & Approach: Analytical, solution-oriented, and comfortable working with both real-time and batch data processing. Strong problem-solving and troubleshooting skills
• Technical Skills:

- Expertise in real-time data processing with Apache Kafka and Pub-Sub
- Proficiency in PostgreSQL and SQL Server for database management and querying
- Experience with dbt for data transformation and modeling
- Strong programming skills in Python for automation and ELT pipelines
- Familiarity with GCP data services (BigQuery, Dataflow, Cloud Composer, Cloud Run)
- Knowledge of DevOps & CI/CD practices for data deployments

• Language Skills: Business fluency in English; additional language skills are a plus

Why join radicant

• Join a Purpose-Driven Bank: Be part of Switzerland's first digital sustainability bank, where every role supports positive change. Make an impact by steering work that aligns with purpose and sustainability 
• Collaborate Internationally: Work alongside a diverse and highly skilled team passionate about innovation and sustainability 
• Flexible Remote Work Options: Enjoy the freedom and tools to work remotely, or join us at our central Lisbon office 
• A Fast-Paced, Fun Culture: We get things done, we have the courage to act and innovate, and always enjoy the journey together!

Are you passionate about our mission and ready to make an impact?
 We’re looking for someone driven, inspired, and excited to grow with us. If that sounds like you, reach out - we’d love to see what you bring to the table.