Beschreibung

Data Analytics Engineer
Swisslinx is supporting a prestigious international financial institution in Basel in the search for an experienced Data Analytics Engineer to join a major data transformation programme.
Data Analytics Engineer
Job description:
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
About the customer:
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.
Requirements:
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 , 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
Compensation benefits:
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. jid335dee2a jit0625a jiy26a