Senior Data Architect with Data Engineering, Finance RnD Platform

About the Position

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.

About the Project

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.

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

Technologies

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