Data Analytics Engineer – Banking IT

Source Group International; Basel; Hybrid; CHF 120,000 - 170,000; Full time

Job summary

Source Group International is seeking an experienced Data Analytics Engineer to join our Banking Technology team in Basel on a 24-month hybrid role. You will develop data pipelines, migrate datasets to an on-premise data lakehouse, with potential cloud migration.

Work closely with business stakeholders, enable advanced analytics and BI, using Python, Spark, and SQL. You will contribute to data architecture and support on-call rotation; 50% onsite, 50% remote, ASAP start.

Qualifications

• 5+ years of experience with modern data technologies.

Responsibilities

• Design, develop and maintain end-to-end data pipelines using Python, Spark and SQL.
• Build and optimise data ingestion and transformation processes.
• Support the migration of existing pipelines from C# to Python.
• Translate business and technical requirements into scalable solutions.
• Contribute to data architecture and technical design.
• Collaborate with business analysts, data architects, engineers and other stakeholders.
• Provide technical support and participate in the shared on-call rotation.

Skills

Python

Data pipelines

Data modelling

Stakeholder management

Communication

Spark

Hadoop

Hive

Kafka

ELK

Tools

dbt

Airflow

NiFi

RunDeck

Cloudera

Apache Iceberg

Job description

Data Analytics Engineer – Banking IT

Location: Basel, Switzerland
Work Model: Hybrid – 50% onsite / 50% remote
Workload: 100%
Contract Duration: 24 months, with potential extension
Start Date: ASAP (candidates with a notice period may be considered)

Role Overview

We are looking for an experienced Data Analytics Engineer to join the Banking Technology team as part of a major data transformation programme.

The role focuses on developing new data pipelines and migrating existing datasets to an on-premise data lakehouse, with potential future migration to the cloud.

You will work with modern data technologies, supporting data management, advanced analytics and business intelligence initiatives in close collaboration with technical and business stakeholders.

Key Responsibilities

• Design, develop and maintain end-to-end data pipelines using Python, Spark and SQL.
• Build and optimise data ingestion and transformation processes.
• Support the migration of existing pipelines from C# to Python.
• Translate business and technical requirements into scalable solutions.
• Contribute to data architecture and technical design.
• Collaborate with business analysts, data architects, engineers and other stakeholders.
• Provide technical support and participate in the shared on-call rotation.

Must-have Requirements

• Minimum 5 years of experience with modern data technologies.
• Strong hands-on experience with Python.
• Proven experience building data pipelines for Data Warehouse, Data Lake or Lakehouse architectures.
• Practical experience with technologies such as Spark, Hadoop, Hive, Kafka, HBase, Impala, dbt or ELK.
• Strong knowledge of data modelling, design patterns and scalable applications.
• Excellent communication and stakeholder management skills.

Nice-to-have Requirements

• Banking or financial services experience.
• Knowledge of financial instruments, trade lifecycle or risk management.
• Experience with Apache Iceberg and Cloudera.
• SQL and NoSQL databases (PostgreSQL, SQL Server, Cassandra, Sybase IQ).
• Workflow orchestration tools such as Airflow, NiFi or RunDeck.
• CI/CD, Agile methodologies and automated testing.
• Previous experience with C#/.NET.
• Cloud platforms such as Databricks, Snowflake or Azure Synapse.
• Microservices and API development (REST/SOAP).

Additional Information

The role includes a shared on-call rotation, one week at a time, Monday to Friday overnight.

We believe in equal opportunity for all and actively encourage applications from diverse backgrounds, experiences, and perspectives.