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.
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
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
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
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
Veröffentlichungsdatum:
30 Jul 2026Standort:
RemoteTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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