Senior Data Architect with Data Engineering, Finance RnD Platform

Aether Biomedical; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Vacation days up to 26 days/year

Health and life insurance

Flexible work arrangements

Learning resources (O’Reilly, LinkedIn

Training and development programs

Internal psychological support

Zusammenfassung

DataArt seeks a Senior Data Architect with strong data engineering capabilities to drive AI-driven, data-intensive initiatives for financial clients. You will blend hands-on engineering with architectural design, supporting proofs of concept and reusable accelerators while shaping modern data capabilities.

You will work with Python, SQL, Spark, Airflow, dbt, and cloud platforms like AWS/Azure/GCP, building scalable data pipelines and collaborating across AI and engineering teams to enable data

Qualifikationen

• Experience working as a Data Architect with engineering background in client facing or product focused environments.
• Hands on experience with modern data platforms, data modeling, and pipeline design.
• Understanding of data integration, transformation, and orchestration patterns.
• Experience building data solutions for analytics, automation, or AI driven use cases.
• Ability to translate business needs into technical implementations.
• Experience with Python and SQL in data engineering contexts.
• Familiarity with at least one major cloud platform such as AWS Azure or GCP.
• Strong problem solving and communication skills.
• Exposure to financial domains such as banking investment or asset management.

Aufgaben

• Design and evolve data architectures for client facing proof of concepts, demos, and accelerator solutions.
• Develop and maintain scalable data pipelines, integrations, and transformation workflows.
• Collaborate with AI and engineering teams to enable data foundations for intelligent and agent driven systems.
• Translate business and client requirements into practical and scalable technical solutions.
• Contribute to the design and development of reusable data products and internal data offerings.
• Support rapid experimentation and delivery of proofs of concept in financial services contexts.
• Ensure data solutions are performant, reliable, and scalable through collaboration with cross functional teams.
• Participate in architecture discussions and contribute to best practices within the data stream.

Kenntnisse

Data architecture

Data engineering

Python

SQL

Communication

Problem solving

Financial domain knowledge

Tools

dbt

Airflow

Docker

Kubernetes

Snowflake

BigQuery

Redshift

Jobbeschreibung

Senior Data Architect with Data Engineering, Finance RnD Platform

Data

Fin RnD is a group within DataArt’s Fin practice focused on accelerating AI adoption for both clients and internal engineering teams. The team builds reusable accelerators and uses them as a foundation for custom proof-of-concepts tailored to client-specific needs, while continuously developing hands‑on expertise with the latest AI technologies.

The group operates across multiple streams, including a Data Stream that is currently being actively developed. This role will be part of that stream and will contribute directly to real client cases, helping shape how data products and offerings are designed and evolved across financial industry accounts.

Position overview

We are looking for a Senior Data Architect with strong data engineering experience to contribute to AI driven and data intensive initiatives for financial clients. You will combine hands on engineering with architectural design, supporting proof of concepts, demos, and reusable accelerators while shaping modern data capabilities within the team.

Python, SQL, Apache Spark, Airflow, dbt, cloud platforms including AWS Azure or GCP, data warehouses such as Snowflake BigQuery or Redshift, REST APIs, Docker, Kubernetes, CI CD pipelines

Responsibilities

Design and evolve data architectures for client facing proof of concepts, demos, and accelerator solutions

Develop and maintain scalable data pipelines, integrations, and transformation workflows

Collaborate with AI and engineering teams to enable data foundations for intelligent and agent driven systems

Translate business and client requirements into practical and scalable technical solutions

Contribute to the design and development of reusable data products and internal data offerings

Support rapid experimentation and delivery of proof of concepts in financial services contexts

Ensure data solutions are performant, reliable, and scalable through collaboration with cross functional teams

Participate in architecture discussions and contribute to best practices within the data stream

Requirements

Experience working as a Data Architect with engineering background in client facing or product focused environments

Hands on experience with modern data platforms, data modeling, and pipeline design

Understanding of data integration, transformation, and orchestration patterns

Experience building data solutions for analytics, automation, or AI driven use cases

Ability to translate business needs into technical implementations

Experience with Python and SQL in data engineering contexts

Familiarity with at least one major cloud platform such as AWS Azure or GCP

Strong problem solving and communication skills

Exposure to financial domains such as banking investment or asset management

Nice to have

Familiarity with AI enabled data products or agent based systems

Experience working in RnD or proof of concept driven environments

Knowledge of containerization and orchestration tools such as Docker and Kubernetes

Experience with modern data stack tools such as dbt Airflow or Spark

What We Offer:

• Vacation days: Up to 26 business days per year.
• 10 illness/special days off per year (fully paid, no medical papers needed) for all contract types
• Health and life insurance (Luxmed)
• MyBenefit platform with Multisport option
• Internal psychological support service
• English language classes from the first working day
• Access to external learning platforms: O’Reilly, LinkedIn Learning, Udemy, and a wide catalog of diverse internal training
• Flexible workplace: work from the office, from home, or choose a hybrid option
• Opportunities to develop as a public speaker, mentor, or technical interviewer
• Fully paid idle (bench) when not involved in a project