Head of Data Technologies Department

"PAŞA Insurance" ASC invites candidates to apply for the position of Head of Data Technologies Department to become a member of a professional team. Key Responsibilities: Strategic Leadership Aligning the management overview, strategy, and roadmap of the platforms with the organization's objectives. Assessing new technologies (cloud-native data platforms, orchestration, MLOps, real-time data streaming) and exploring implementation opportunities. Ensuring standardization, best practices, and governance across RDBMS, DataOps, and MLOps functions. Managing and developing a multidisciplinary team consisting of DBAs, DataOps engineers, platform engineers, and MLOps specialists. Enhancing cooperation with cross-functional stakeholders (Data Science, Analytics, Information Security, Business units). Creating opportunities for career development for team members and ensuring ongoing skill enhancement. Management of Platform and Infrastructure: Ensuring performance, reliability, recovery, and compliance of traditional databases (MS SQL, PostgreSQL). Managing and optimizing modern data ecosystem components (MinIO, Trino, Iceberg, Spark, Airflow, Kafka, Dataiku) for efficiency. Establishing frameworks for scalability, monitoring, automation, and cost management of platforms. Integrating platforms with other systems of the enterprise and security frameworks. Operational Improvements: Defining and ensuring SLA, SLO, and KPI regarding platform reliability and data accessibility. Implementing proactive monitoring, alerting, and incident response processes. Implementing capacity planning, performance tuning, and cost management. Increasing automation in provisioning, deployment, and maintenance processes. Application of MLOps and DataOps: Strengthening collaboration between Data Science and IT teams to ensure the transition of ML models into production environments. Establishing model versioning, CI/CD pipelines, reproducibility, and monitoring processes. Accelerating data flows and reducing the time for generating analytic value by applying DataOps approaches. Management, Security, and Compliance: Ensuring compliance with data security, privacy, and regulatory requirements. Implementing access control, encryption, and audit frameworks in collaboration with Information Security. Establishing governance processes to track data quality, lineage, and lifecycle.