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Strong employer brand and broad, in-demand data skills increase competition despite seniority.
Core data engineering and cloud skills are broadly transferable across industries.
Extensive mandatory data platform, cloud, and leadership skills create strict technical and managerial filters.
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Lead and manage a data engineering team responsible for designing, building, and maintaining scalable data pipelines, ETL workflows, and data architecture across cloud and on-prem platforms.
Drive modernization initiatives on cloud-native platforms, especially Azure Cloud, Databricks, Airflow/Azure Data Factory/Synapse Pipelines, and event-driven systems like Kafka and Azure Event Hub.
Ensure operational excellence including system reliability, monitoring infrastructure utilization, incident management, and delivery management with regular status reporting.
Experience in big data engineering, data platform management, and cloud migration to platforms preferably Azure.
Proficiency in Python, advanced SQL, ETL development, database development (Oracle, MySQL, PostgreSQL, SQL Server), UNIX/Shell scripting, JSON/API integrations, and event streaming systems such as Kafka or Azure Event Hub.
Demonstrated leadership experience managing teams, including capacity planning, technical coaching, and delivery management in complex environments.
Work Experience Required: Not explicitly mentioned in the JD. Notice period: Not explicitly mentioned in the JD.
Hands-on technical leader with strong expertise in modern data engineering, cloud migration (Azure preferred), and AI-enabled automation tools.
Experienced in balancing strategic vision with hands-on technical leadership, making independent decisions, and driving architecture direction.
Capable of managing cross-functional collaboration and stakeholder communication across distributed teams and multiple time zones.