Track Manager - Kubernetes, Terraform

Data Pipeline Engineering: Develop and execute robust API, MCP (Model Context Protocol), and sFTP data ingestions from core IT and business platforms.\r\n* Databricks ODS Architecture: Design, optimize, and maintain data schemas, models, and tables within Databricks using Delta Lake and Medallion architecture (Bronze/Silver/Gold).\r\n* Data Mapping & Lineage: Map source system infrastructure to establish clear technical data lineage from raw application logs to the analytics layer.\r\n* Workflow Automation: Program and manage automated orchestration schedules using Databricks Workflows, Apache Airflow, or cron-based pipelines.\r\n* Performance Reporting Support: Deliver clean, structured, and highly performance data layers optimized for end-user BI dashboard consumption (e.g., Power BI, Tableau).

Data Platforms: 3+ years of hands-on experience building production data pipelines in Databricks using PySpark, Scala, or Advanced SQL.\r\n* Integration Techniques: Proven expertise developing custom REST API clients, handling sFTP secure transfers via script, and utilizing MCP for contextual data synchronization.\r\n* Data Modeling: Strong foundation in data warehouse modeling, schema evolution, and managing operational data stores (ODS).\r\n* Domain Knowledge: Familiarity with IT Service Management (ITSM) telemetry data, application performance monitoring (APM) tools, or core platform log schemas is a plus.\r\n