Data Analytics Engineer

This is an exciting opportunity to work on the evolution of a modern data platform, helping to deliver advanced analytics, real-time data processing, and scalable data solutions that support critical banking operations. You will play a key role in building and enhancing data pipelines, implementing new datasets, and contributing to the migration towards a modern lakehouse architecture.

Working closely with business stakeholders, data architects, analysts, and engineers, you will help shape the future of data capabilities within a highly collaborative and international environment.

• Design, develop and maintain scalable end-to-end data pipelines and data products
• Build robust ETL/ELT solutions for data warehouse and data lake/lakehouse environments
• Collaborate with business analysts and stakeholders to gather, refine and translate requirements into technical solutions
• Develop high-quality, maintainable code using modern software engineering practices
• Contribute to data architecture, platform design and technical decision-making
• Implement data integration, transformation and validation processes across multiple data sources
• Support real-time and batch data processing initiatives
• Participate in proof-of-concept activities and evaluation of emerging data technologies
• Ensure solutions meet security, governance, data retention and performance requirements
• Support production environments, including participation in an on-call rotation

• Minimum 5 years of experience in Data Engineering, Big Data Engineering, or Analytics Engineering roles
• Strong experience designing and developing data ingestion and processing pipelines
• Hands-on experience with modern data platforms and technologies such as: Spark, Flink, Kafka or similar distributed processing frameworks, Hadoop ecosystem technologies including Hive, HBase, Impala or equivalen or lakehouse technologies such as Apache Iceberg
• Strong programming skills in Python, Java or C#
• Excellent understanding of data modelling, scalable system design and data architecture principles
• Strong SQL development skills and experience working with relational and/or NoSQL databases
• Experience within Investment Banking, Capital Markets, Financial Services, Risk, Trading or Market Data environments is mandatory
• Fluent in English

Nice to have:

• Experience with workflow orchestration tools such as Airflow, NiFi or RunDeck
• Exposure to CI/CD pipelines and modern software delivery practices
• Experience working in Agile environments (Scrum/Kanban)
• Knowledge of automated testing, debugging and performance optimisation
• Experience with cloud-based data platforms such as Databricks, Azure Synapse or Snowflake
• Understanding of microservices and API technologies

• Long-term contract for 24 months with a highly respected international financial institution (strong chance to extend up to five years due to project timelines)
• Opportunity to work on large-scale data transformation initiatives
• Exposure to modern data technologies and enterprise-scale data platforms
• Collaborative and intellectually stimulating environment
• Competitive contract package
•  50/50 split WFH/home office per week (and possibility to work abroad 20 days per year)

If you possess strong Data Engineering expertise combined with experience in financial services and modern data platforms, we would be pleased to hear from you before the deadline on 16 June.