Job Summary
Data Engineer or Technical Data Architect – IT Service & Platform Analytics
Key Responsibilities
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).
Skill Requirements
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
Other Requirements
Dickson\\\'s Cloudability Additional Position