Gautam Buddha Nagar, Uttar Pradesh
Job Summary
Data Engineer or Technical Data Architect – IT Service & Platform Analytics
Data Engineer or Technical Data Architect – IT Service & Platform Analytics\\\\r\\\\n\\\\r\\\\nRole Overview\\\\r\\\\n• Designs, builds, and maintains data pipelines that feed performance metrics into the Databricks Operational Data Store (ODS). This role maps source systems, develops robust data schemas, and automates integrations across business applications, IT services, and core platforms to enable real-time performance reporting for Apptio Bill of IT and IT performance reporting dashboards delivered via Power BI\\\\r\\\\n \\\\r\\\\nCore Responsibilities\\\\r\\\\n• 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).\\\\r\\\\n \\\\r\\\\nTechnical Qualifications\\\\r\\\\n• 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.
Key Responsibilities
Data Pipeline Engineering: Develop and execute robust API, MCP (Model Context Protocol), and sFTP data ingestions from core IT and business platforms. • Databricks ODS Architecture: Design, optimize, and maintain data schemas, models, and tables within Databricks using Delta Lake and Medallion architecture (Bronze/Silver/Gold). • Data Mapping & Lineage: Map source system infrastructure to establish clear technical data lineage from raw application logs to the analytics layer. • Workflow Automation: Program and manage automated orchestration schedules using Databricks Workflows, Apache Airflow, or cron-based pipelines. • 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. • Integration Techniques: Proven expertise developing custom REST API clients, handling sFTP secure transfers via script, and utilizing MCP for contextual data synchronization. • Data Modeling: Strong foundation in data warehouse modeling, schema evolution, and managing operational data stores (ODS). • Domain Knowledge: Familiarity with IT Service Management (ITSM) telemetry data, application performance monitoring (APM) tools, or core platform log schemas is a plus.
Other Requirements
Dickson\'s Cloudability Additional Position
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