Data Engineer - Financial Services

Michael Page

Nyon

Hybrid

CHF 110.000 - 150.000

Vollzeit

vor 47 Stunden
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Benefits dieser Stelle

Home office
Flexibility

Zusammenfassung

Michael Page in Nyon is seeking a Data Engineer - Financial Research to join a growing data/tech initiative at the intersection of financial markets and data engineering. You will help build a proprietary data ecosystem, supporting a team of analysts, and contribute to infrastructure, databases, and analytical tools enhancing efficiency and scalability.

Collaborating with investment professionals, you will deliver innovative data solutions to collect, organize, and leverage financial

Qualifikationen

  • Bachelor's or Master's in CS, Data Engineering, Software Engineering, Data Science, Mathematics, or related discipline.
  • Strong knowledge of Python and SQL.
  • Experience building and maintaining databases, data pipelines, and data processing workflows.
  • Understanding of modern data architectures, cloud technologies, and data engineering best practices.
  • Familiarity with platforms such as Snowflake, Databricks, Azure, AWS, or similar technologies would be advantageous.
  • Strong analytical and problem-solving skills.
  • Ability to communicate effectively with both technical and non-technical stakeholders.
  • Self-starter mindset with a strong willingness to learn and build.
  • French and English

Aufgaben

  • Design, build, and maintain proprietary databases supporting financial research activities.
  • Participate in the creation and evolution of a centralized data lake.
  • Contribute to the implementation and development of modern data architectures, including platforms such as Snowflake.
  • Develop and manage scalable data pipelines to acquire, transform, validate, and distribute data from multiple sources.
  • Ensure data quality, integrity, governance, and accessibility across the research platform.
  • Continuously improve the firm's data infrastructure to support future growth and analytical capabilities.
  • Develop proprietary tools to improve analyst productivity and research effectiveness.
  • Build screening and data exploration solutions to support investment research workflows.
  • Automate data collection, processing, and reporting tasks.
  • Translate research requirements into practical and scalable technology solutions.
  • Work closely with end users to identify opportunities for innovation and continuous improvement.

Kenntnisse

Python
SQL
Data pipelines
Databases
Cloud platforms

Ausbildung

Bachelor's or Master's in CS/Data Engineering

Tools

Snowflake
Databricks
Azure
AWS

Jobbeschreibung

About Our Client

Our client is located in Nyon. This role offers a unique opportunity to help build a proprietary data ecosystem from the ground up, supporting a team of fundamental research analysts. The successful candidate will contribute to the development of the infrastructure, databases, and analytical tools that will enhance the efficiency, depth, and scalability of the research process.

  • Data plateform
  • Dynamic environment
About Our Client

Our client is located in Nyon. This role offers a unique opportunity to help build a proprietary data ecosystem from the ground up, supporting a team of fundamental research analysts. The successful candidate will contribute to the development of the infrastructure, databases, and analytical tools that will enhance the efficiency, depth, and scalability of the research process.

Working closely with investment professionals, the Data Engineer will play a key role in delivering innovative solutions that transform the way financial information is collected, organized, and leveraged.

Job Description

Our client is seeking a highly motivated Data Engineer - Financial Research to join a growing research and technology initiative at the intersection of financial markets, data engineering, and artificial intelligence.

This role offers a unique opportunity to help build a proprietary data ecosystem from the ground up, supporting a team of fundamental research analysts. The successful candidate will contribute to the development of the infrastructure, databases, and analytical tools that will enhance the efficiency, depth, and scalability of the research process.

Working closely with investment professionals, the Data Engineer will play a key role in delivering innovative solutions that transform the way financial information is collected, organized, and leveraged.

Data Platform Development
  • Design, build, and maintain proprietary databases supporting financial research activities.
  • Participate in the creation and evolution of a centralized data lake.
  • Contribute to the implementation and development of modern data architectures, including platforms such as Snowflake.
  • Develop and manage scalable data pipelines to acquire, transform, validate, and distribute data from multiple sources.
  • Ensure data quality, integrity, governance, and accessibility across the research platform.
  • Continuously improve the firm's data infrastructure to support future growth and analytical capabilities.
Research Tools & Analytics
  • Develop proprietary tools aimed at improving analyst productivity and research effectiveness.
  • Build screening and data exploration solutions to support investment research workflows.
  • Automate data collection, processing, and reporting tasks.
  • Translate research requirements into practical and scalable technology solutions.
  • Work closely with end users to identify opportunities for innovation and continuous improvement.
Innovation & Artificial Intelligence
  • Evaluate emerging technologies relevant to financial research and data analysis.
  • Contribute to the adoption of artificial intelligence and automation capabilities across research workflows.
  • Assess opportunities to leverage external SaaS solutions while helping develop proprietary alternatives when appropriate.
  • Support the creation of differentiated research capabilities through the intelligent use of data and technology.
The Successful Applicant
  • Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, Data Science, Mathematics, or a related discipline.
  • Strong knowledge of Python and SQL.
  • Experience building and maintaining databases, data pipelines, and data processing workflows.
  • Understanding of modern data architectures, cloud technologies, and data engineering best practices.
  • Familiarity with platforms such as Snowflake, Databricks, Azure, AWS, or similar technologies would be advantageous.
  • Strong analytical and problem-solving skills.
  • Ability to communicate effectively with both technical and non-technical stakeholders.
  • Self-starter mindset with a strong willingness to learn and build.
  • French and English
What's On Offer

Attractive environment.
Home office and flexibility

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