2606413 Data Analytics Engineer – Banking IT

Swisslinx AG; Basel; Hybrid; CHF 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Hybrid work arrangement

International environment

Zusammenfassung

Swisslinx AG is seeking a data engineer to shape a modern data platform for banking operations, building scalable data pipelines and contributing to a lakehouse transition. You will collaborate with business stakeholders, data architects, analysts and engineers to deliver data solutions with wide impact.

You will design end-to-end pipelines, implement ETL/ELT, and participate in PoCs while ensuring security, governance and performance requirements across production environments.

Qualifikationen

• 5+ years of professional experience in data engineering or analytics engineering.
• Strong experience designing and developing data ingestion and processing pipelines.
• Practical experience with Spark, Flink, Kafka, Iceberg, or comparable lakehouse tools.
• Familiarity with Hadoop ecosystem technologies such as Hive, HBase or Impala.
• Strong programming skills in Python, Java or C#; solid data modelling and architecture knowledge.
• Strong SQL skills and experience with relational or NoSQL databases.
• Experience in banking, capital markets, or financial services is a plus.
• Fluency in English; collaborative and proactive communication style.

Aufgaben

• Design, develop and maintain scalable, end-to-end data pipelines and data products.
• Build ETL/ELT solutions for data warehouse, data lake and lakehouse environments.
• Collaborate with business analysts and stakeholders to translate needs into technical solutions.
• Write high-quality, maintainable code using modern software engineering practices.
• Contribute ideas to data architecture, platform design and technical decisions.
• Implement data integration, transformation and validation across sources.
• Support both real-time and batch data processing initiatives.
• Participate in PoCs and evaluate emerging data technologies.
• Ensure security, governance, retention, performance and quality requirements.
• Help support production environments as part of a shared on-call rotation.

Kenntnisse

Python

Java

C#

SQL

English Fluency

Tools

Spark

Flink

Kafka

Apache Iceberg

Hadoop Hive

HBase

Impala

Databricks

Snowflake

Azure Synapse

Jobbeschreibung

In this role, you will help shape the evolution of a modern data platform that supports critical banking operations. You will build and enhance data pipelines, introduce new datasets and contribute to the transition towards a scalable lakehouse architecture.

You will join a collaborative, international environment where different perspectives are valued. Working closely with business stakeholders, data architects, analysts and fellow engineers, you will have the opportunity to influence technical decisions and deliver data solutions with meaningful, organisation-wide impact.

• Design, develop and maintain scalable, end-to-end data pipelines and data products
• Build reliable ETL/ELT solutions for data warehouse, data lake and lakehouse environments
• Partner with business analysts and stakeholders to understand their needs and translate them into effective technical solutions
• Write high-quality, maintainable code using modern software engineering practices
• Contribute your ideas to data architecture, platform design and technical decision-making
• Implement data integration, transformation and validation processes across multiple data sources
• Support both real-time and batch data-processing initiatives
• Participate in proof-of-concept projects and evaluate emerging data technologies
• Ensure solutions meet security, governance, retention, performance and quality requirements
• Help support production environments as part of a shared on-call rotation

Requirements

We encourage you to apply even if you do not meet every requirement listed. Relevant experience may have been gained through different roles, industries or career paths:

• Substantial professional experience in data engineering, big data engineering or analytics engineering—typically five years or more
• Strong experience designing and developing data-ingestion and processing pipelines
• Practical experience with one or more modern data technologies, such as Spark, Flink, Kafka, Apache Iceberg, or comparable distributed-processing and lakehouse tools
• Familiarity with relevant Hadoop ecosystem technologies, such as Hive, HBase or Impala, or equivalent platforms
• Strong programming skills in at least one of the following: Python, Java or C#
• A solid understanding of data modelling, scalable system design and data architecture
• Strong SQL skills and experience with relational or NoSQL databases
• Experience in investment banking, capital markets, financial services, risk, trading or market-data environments
• A collaborative and proactive approach, with the ability to communicate clearly across technical and non-technical teams
• Fluency in English

The following would be beneficial, but you do not need to have all—or any—of these to apply:

• Knowledge of financial instruments, trade lifecycles or risk management
• Experience analysing, implementing or testing financial data products
• Experience with Cloudera
• Knowledge of Apache Iceberg
• Experience with Databricks, Snowflake or Azure Synapse
• Understanding of microservices architecture
• Experience creating or managing REST or SOAP APIs
• Experience with .NET or C#
• A 24-month contract with a highly respected international financial institution
• Strong potential for extension, with the wider programme expected to continue for up to five years
• The opportunity to make a visible contribution to a major data-transformation initiative
• Exposure to modern technologies and enterprise-scale data platforms
• A collaborative, international and intellectually stimulating working environment
• A hybrid working arrangement, with an approximately 50/50 split between working from home and on-site work
• The possibility of working abroad for up to 20 days per year

If you are excited by the opportunity but are unsure whether your experience matches every point, we would still be pleased to hear from you. We welcome applications from people with diverse backgrounds, experiences and perspectives.

Maybe not for you, but for someone else?