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Metro location, strong employer brand, and broad data engineering skillset increase applicant competition.
Core data engineering and cloud skills are broadly transferable across industries.
Multiple mandatory technical skills, cloud/Databricks requirements, and managerial expectations make shortlisting stringent.
Lead and mentor a data engineering team responsible for scalable data architecture, ETL pipelines, and data processing systems across cloud and on-prem platforms.
Oversee modernization initiatives on Azure Cloud, including Databricks, Airflow/Azure Data Factory, event-driven systems like Kafka and Azure Event Hub.
Manage operational excellence of production data systems, including incident response, system performance, and process efficiency improvements.
Experience Required: Not explicitly mentioned in the JD (implied managerial and hands-on data engineering experience).
Strong Big Data Engineering and Data Platform Management skills with expertise in Python, advanced SQL, ETL development, and database development (Oracle, MySQL, PostgreSQL, SQL Server).
Experience with cloud platforms, preferably Azure, including data migration to cloud and event streaming systems like Kafka or Azure Event Hub.
Technical proficiency in UNIX/Shell scripting, JSON/API integrations, and Master Data Management (MDM).
Hands-on technical leader with track record in modern data engineering and cloud migration, especially on Azure platform.
Demonstrated ability to drive AI-enabled automation adoption and lead high-performing teams with strong technical coaching skills.
Capable of balancing strategic transformation leadership with operational management and stakeholder communication skills in a distributed team environment.