Description

You will own the Azure Databricks Lakehouse architecture and lead data engineering efforts for a 16-week project delivering validated ETL pipelines, analytical models, and MicroStrategy dashboards.

This role is on-site.

Responsibilities

• Architect the Bronze/Silver/Gold data layers, defining ingestion patterns for daily-batch processing and optimizing the Gold model for MicroStrategy KPI consumption.
• Lead technical analysis of ERP sources (SAP, Field Service, Telematics) and design ETL pipelines in Azure Databricks to ensure data quality and consistency.
• Partner with reporting teams to configure functional security and optimize metrics for three user profiles: Field Technician, Service Manager, and Scheduler.
• Lead data validation, coordinate functional testing and user validation sessions, and support production deployment and project closure documentation.
• Coordinate with client stakeholders for scope definition, KPI prioritization, and issue resolution while maintaining technical quality standards.

Required Skills

• 10+ years in data architecture/engineering, including 5+ years leading Azure Databricks Lakehouse implementations.
• Hands-on experience with PySpark, Spark SQL, and Delta Lake modeling across the full solution lifecycle.
• Deep understanding of SAP ERP/ECC and/or S/4HANA data structures, including FI/CO, MM, BAPIs, BAPIs, and IDOCs.
• Proven ability to design and implement ETL pipelines and orchestration in enterprise environments.
• Experience with Azure cloud services and API integration.
• Strong background in data modeling, data quality governance, and performance tuning.
• Bachelor's degree in a relevant technical field.

Preferred Skills

• Experience optimizing data models specifically for MicroStrategy reporting.
• Background in implementing Lakehouse patterns for operational KPIs and SLA tracking.

Key Skills

Education

Bachelor's degree