Senior Data Architect with Data Engineering, Finance RnD Platform

Project Overview

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.

Technology Stack

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, and 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 an 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

• Up to 26 business vacation days per year.
• 10 fully paid illness/special days off per year, with no medical papers required, for all contract types.
• Health and life insurance (Luxmed).
• MyBenefit platform with a Multisport option.
• Internal psychological support service.
• English language classes from the first working day.
• Access to O’Reilly, LinkedIn Learning, Udemy, and a wide catalog of internal training.
• Flexible workplace: office, home, or hybrid work.
• Tech Skills Mentoring Program.
• Opportunities to develop as a public speaker, mentor, or technical interviewer.
• Fully paid bench time when not involved in a project.
• Certification reimbursement for AWS, GCP, Microsoft, and other certifications.