Head of Data Technology division

Responsibilities Align and execute the vision, strategy, and roadmap for platforms administration with organizational goals. Evaluate and recommend adoption of new technologies (cloud-native data platforms, orchestration, MLOps, real-time data streaming). Ensure standardization, best practices, and governance across RDBMS, DataOps, and MLOps functions. Lead and develop a multidisciplinary team of DBAs, DataOps engineers, platform engineers, and MLOps specialists. Foster collaboration with cross-functional stakeholders (Data Science, Analytics, IT Security, Business Units). Oversee administration of relational databases (MS SQL, PostgreSQL) for performance, availability, disaster recovery, and compliance. Govern and optimize modern data stack components (MinIO, Trino, Iceberg, Spark, Airflow, Kafka, Dataiku) for ingestion, storage, processing, and analytics. Establish frameworks for platform scalability, monitoring, automation, and cost management. Ensure integration of platforms with enterprise systems and security frameworks. Define and enforce SLAs, SLOs, and KPIs for platform reliability and data availability. Implement proactive monitoring, alerting, and incident response processes. Lead capacity planning, performance tuning, and cost management initiatives. Drive automation in provisioning, deployment, and maintenance processes. Enable seamless collaboration between Data Science and IT teams for operationalizing ML models. Establish model versioning, CI/CD pipelines, reproducibility, and monitoring processes. Adopt modern DataOps practices to accelerate data workflows and reduce time-to-insight. Ensure compliance with data security, privacy, and regulatory requirements. Work with Information Security to implement access control, encryption, and audit frameworks. Establish governance processes for data quality, lineage, and lifecycle management. Knowledge and Skills Deep expertise in database administration (MS SQL, PostgreSQL) and modern big data ecosystems. Experience with orchestration (Airflow), distributed systems (Spark, Kafka), and data storage (Iceberg, MinIO). Hands-on experience with MLOps tools (Dataiku, MLflow, Kubeflow, or similar). Proven success in building and scaling technical teams. Excellent leadership, communication, and stakeholder management skills. Language skills: Azerbaijani, English, Russian Education and Experience Master's or Bachelor's degree in Computer Science, Information Systems, or related field. At least 7 years of experience in data/platform engineering, with 3+ years in leadership roles. What we offer Collaborative and growth-oriented environment within a professional multidisciplinary team. Support and opportunities for personal and professional development. Exposure to innovative technologies and advanced approaches. Corporate culture based on transparency and mutual respect. Opportunity to work in a "Great Place To Work" certified company.