Sber is looking for a Chief Data Officer for the "People and Culture" block.

The team is developing the data platform for the "People and Culture" block. They create Data Products that form the basis for:

• Comprehensive HR analytics — from operational reports to predictive research;
• In-depth human resources research — analysis of retention, mobility, training effectiveness;
• Advanced ML models — churn prediction, recruitment, motivation, career paths;
• B2E agent for Sber employees.

Data helps make informed HR decisions based on real metrics, not intuition.

Technological Context:

The "Puls" system is a single point of interaction for every Sber employee with the company. It is a set of systems with a microservice architecture, including a data warehouse on ClickHouse, DataLake on S3 and Trino, ETL on Kafka and AirFlow, a data catalog, and a Semantic Layer. The main development focus is on multi-agent systems (Multi-agent AI), where data serves as fuel for LLM agents that automate routine tasks and assist in HR decision-making.

Responsibilities:

You will become the architectural and process leader in the data domain for the "People and Culture" block, responsible for the strategy, quality, and development of platform solutions, data strategy, and architecture:

• Develop and implement the block's data management strategy, ensuring the development of the "Puls" architecture: from the Raw data layer to Master data marts.
• Design a multi-layered storage architecture, based on methodologies.
• Define priorities and pace for data infrastructure development and the implementation of modern Data Solutions.

Process and Quality Management:

• Establish data management processes: implement data contracts, build a role model.
• Approve unified access rules to the block's information resources and data exchange standards.
• Ensure a high level of data quality (profiling, validation, monitoring) and prevent security breaches.

AI and Innovation (Multi-agent Systems):

• Ensure the support and development of the AI Semantic Layer and knowledge graph — the foundation for LLM context and agents.
• Integrate artificial intelligence and machine learning into data processing (RAG pipelines, vector search).
• Define data quality requirements for training ML models and operating multi-agent systems.

Regulation and Leadership:

• Ensure compliance of data processing with 152-FZ and personal data protection principles at all stages of the life cycle.
• Test company-wide requirements for the block's objectives and align strategies with the management of the "Research and Analytics" Division.
• Advise clients and adjacent teams on selecting optimal data structures and their transfer formats.

Requirements:

• Have a deep understanding of modern Data Warehouse (DWH), Data Lake architectures, and data mart construction principles.
• Have practical experience in designing ETL/ELT processes (Kafka, Airflow). You must clearly understand the difference between layers: Raw data, Detailed Storage (DDS), and Marts.
• Understand the concepts of Master Data Management (MDM), Data Governance, Data Lineage, and Data Catalog. Experience implementing or administering at least one of these tools is desirable.
• Know and understand the operation of Sber's stack: ClickHouse (OLAP), Trino (distributed SQL), S3 (DataLake), Kafka (data streams).
• Have experience working with graph databases or an understanding of Property Graph models will be a significant advantage.
• Know flexible development methodologies (Scrum, Kanban, SAFe) and be able to apply them to data products and ML pipelines.
• Be familiar with Domain-Driven Design and the Sber ecosystem.
• Understand the principles of working with personal data (152-FZ) and have experience in data auditing or protection.
• Have experience working in the banking sector or fintech, and understand Enterprise Web Services (EWS) processes.
• Possess a high degree of autonomy and responsibility for results.
• Possess systemic thinking: the ability to see not only the local task but also its impact on adjacent processes, integrations, and the bank's overall architecture.
• Have strong communication skills: the ability to negotiate with difficult stakeholders, to argue your position to both business and technical leadership.
• Be energetic and initiative-taking — ready to lead the team and drive change in a large corporate environment.

Conditions:

• Office-based work format, office address: Kutuzovsky Prospekt 32.
• Annual salary review, quarterly and annual bonuses.
• Corporate gym and lounge areas.
• Over 400 educational programs from SberUniversity for professional and career development.
• Adaptation program and supervisor support at the start.
• Extended voluntary medical insurance, preferential insurance for family, and a corporate pension program.
• Flexible mortgage discount equal to 1/3 of the Central Bank's key rate.
• Prime subscription with the possibility of shared use by three close individuals.
• Referral bonus for recommending friends to the Sber team.