We are looking for a Risk Data Governance Lead to own and transform our risk data infrastructure into an LLM-agent-ready state.

This is a unique role at the intersection of data engineering, data governance, and risk analytics — you will ensure that both humans and AI agents can reliably consume, query, and act on our risk data.

You will lead a small team of analytics engineers and serve as an agent of change across departments — pushing for data quality, enforcing standards, and building the foundation that enables the entire risk function to scale. As we expand to new countries, you will design the group-wide data governance framework from the ground up.

Challenges that await you:

• Lead risk data infrastructure to LLM-agent-ready state. Own the full stack of data quality across 40+ analytical tables in Snowflake, spanning 4 product lines and multiple provisioning frameworks (MxGAAP, IFRS, internal). Define and enforce SLAs, build observability for datamarts across all DMBOK quality dimensions (freshness, completeness, accuracy, consistency, timeliness, validity, uniqueness), and drive metadata and lineage completeness. Choose and maintain the right tooling (Git-based, wiki, or hybrid) for documenting schemas, business concepts, query patterns, and pitfalls
• Design and evolve the LLM context layer. We already maintain a structured knowledge base covering risk data tables, business concept definitions, and query patterns — your job is to scale and formalize this into a production-grade context layer that AI agents can autonomously consume. You will shape how both humans and machines reliably query, interpret, and act on the same data infrastructure
• Be an agent of change across departments. Lead by example in interactions with DWH, Finance, and other teams. Create data quality requirements, push for standards adoption, and translate risk analytics needs into concrete data platform requirements. You represent risk’s data interests externally
• Lead a team of 2–3 analytics engineers. Manage their work, grow their skills, and ensure delivery on datamart development, ETL pipelines, and data quality initiatives. Build a culture of ownership and technical excellence within the team
• Build a group-wide risk data governance framework. As Plata expands into new countries, design and implement data governance standards that scale across geographies. Define reusable patterns for risk data infrastructure that can be rolled out to new markets. The scope of both the framework and the team will grow with the company

What makes you a great fit:

• 5+ years in data engineering, analytics engineering, or data governance roles
• Experience leading or mentoring a small technical team (2–5 people)
• Strong SQL skills and hands-on experience with Snowflake or comparable cloud data warehouses (BigQuery, Redshift)
• Experience with dbt or similar transformation frameworks — we use dbt in production and you will govern the transformation layer
• Track record of driving data quality improvements in a cross-functional environment
• Experience building or maintaining data documentation, metadata catalogs, or knowledge bases
• Hands-on experience with LLM/AI agents and a clear understanding of what makes data infrastructure agent-consumable — you will build this into the foundation of the role
• Comfortable operating in a fast-moving environment with ambiguity — you define the standards, not just follow them
• B2 or higher English level for effective communication with an international team

Nice to have

• Experience in risk management, banking, or fintech data
• Familiarity with Airflow or similar orchestration tools
• Experience with regulatory data requirements (CNBV, IFRS 9, Basel)
• Russian language skills (many team members are Russian-speaking)
• Experience building data governance frameworks across multiple countries or business units