Description

Key Responsibilities

Architecture & Strategy

• Own the Azure Databricks Lakehouse architecture across Bronze/Silver/Gold layers and ensure alignment to corporate standards and best practices.
• Define ingestion and transformation patterns for daily‑batch processing; optimize the Gold model for MicroStrategy consumption and KPI calculations.
• Govern architecture decisions, ensure technical quality, and coordinate with client teams to maintain security, data quality, and compliance with enterprise governance.

Data Engineering & Modeling

• Lead technical analysis of ERP (e.g., SAP), Field Service, Telematics, and other operational sources; define ingestion approaches.
• Design/develop ETL pipelines in Azure Databricks, implementing transformations in Bronze/Silver to ensure consistency and data quality.
• Design/implement the Gold analytical model with the business rules needed to compute prioritized operational KPIs.

Reporting & Analytics Enablement

• Partner with reporting teams to optimize the Gold layer for MicroStrategy (metrics, attributes, calculated indicators) and configure functional security per organizational structure.
• Ensure dashboard design supports three user profiles:
  • Field Technician Experience (daily activity, travel distance, MTTR, completed orders, repeat visits)
  • Service Manager / Supervisor (SLA compliance, closure productivity, first‑time resolution, average completion by type)
  • Scheduler / Dispatcher (assignment efficiency, rescheduling, utilization, availability)

Testing, Validation & Deployment

• Lead data validation/reconciliation, coordinate functional testing and user validation sessions, and support production deployment activities.
• Produce and deliver the Project Closure Document (developments summary, source list, KPI catalog, validation evidence, deployment confirmation).

Stakeholder & Project Leadership

• Coordinate closely with client stakeholders for scope definition, KPI prioritization, and functional validation, providing proactive status/risk updates and issue resolution.
• Ensure team availability vs. schedule, access management, and adherence to documentation standards across the project.

Deliverables & Acceptance (aligned to SOW)

1. ETL Pipelines (Bronze/Silver) Operational and validated in designated environments. Acceptance: pipelines operational and validated.
2. Analytical Data Model (Gold) + KPI Definitions — Formalized, implemented business rules, functionally validated KPIs. Acceptance: functional validation complete.
3. MicroStrategy Dashboard — Profile‑based dashboards (Technician, Supervisor, Scheduler) with metrics/attributes/security per standards. Acceptance: functional validation by designated users.
4. Final Validation & Production Support + Project Closure Document — Includes dev summary, source catalog, KPI catalog, validation evidence, and deployment confirmation. Acceptance: formal project closure.

Schedule & Milestones (16 weeks total)

• M1 (Week 8): ETL pipelines & transformations validated in Bronze/Silver (Deliverable 1).
• M2 (Week 12): Gold analytical model + KPI implementation validated (Deliverable 2).
• M3 (Week 14): MicroStrategy dashboards designed, developed, functionally validated (Deliverable 3).
• M4 (Week 16): Final validation, production deployment support, and Project Closure Document delivered (Deliverable 4).

Qualifications

Must‑Have Experience

• 10+ years in data architecture/engineering, including 5+ years leading Azure Databricks Lakehouse implementations using Bronze/Silver/Gold patterns in enterprise environments.
• Hands-on Azure Databricks implementation experience across the full lifecycle: solution architecture, source analysis, ingestion design, PySpark/Spark SQL development, Delta Lake modeling, orchestration, testing, deployment, production support, and performance tuning.
• SAP project implementation experience with SAP ERP/ECC and/or S/4HANA data in large-scale data, analytics, reporting, or lakehouse initiatives; must understand how SAP business processes and data structures translate into enterprise data models and KPI logic.
• SAP data integration expertise including practical experience extracting, ingesting, mapping, and reconciling SAP data through relevant mechanisms such as SAP tables/views, CDS views, OData/APIs, IDocs, BAPIs, SAP BW/BW/4HANA extracts, flat files, or enterprise integration layers.
• Relevant SAP functional data knowledge across operational and financial domains such as Work Orders, Notifications, Equipment/Assets, Materials, Cost Centers, General Ledger, Service/Field Operations, Plant Maintenance/Customer Service, FI/CO, MM, PM/CS, and/or IS-U, depending on the client landscape.
• Big Data project implementation experience delivering high-volume data platforms using Spark, Delta Lake, cloud data lakes/lakehouses, distributed processing, batch and/or near-real-time ingestion, partitioning, indexing/clustering, data optimization, and scalable transformation frameworks.
• Hands-on ETL/ELT development in Azure Databricks using Spark/Delta Lake, including daily-batch processing, incremental/CDC patterns where applicable, schema evolution, error handling, data quality controls, and intermediate model adaptation.
• Gold-layer analytical modeling experience with proven ability to design business-ready data products, star/snowflake or dimensional models, KPI calculation logic, semantic layers, and BI-ready structures optimized for MicroStrategy or comparable enterprise BI platforms.
• Cross-system source expertise across SAP/ERP, Field Service, Telematics, scheduling/dispatching, workforce, asset, and other operational sources; strong ability to define source-to-target mappings, business rules, reconciliation logic, and master/reference data alignment.
• Enterprise data governance and security mindset including alignment to corporate standards for architecture, data modeling, data quality, lineage, access control, functional security, privacy, compliance, and production readiness; experience with Azure/Databricks governance capabilities such as Unity Catalog is preferred.
• Implementation leadership as a Technical Lead/Coordinator responsible for stakeholder facilitation, requirements clarification, sprint/backlog coordination, technical issue resolution, risk management, cutover planning, status reporting, validation, documentation, and milestone delivery.
• Strong documentation and validation discipline including architecture/design documentation, source catalogs, data dictionaries, KPI catalogs, data lineage, test plans, reconciliation evidence, deployment notes, and project closure documentation.

Nice‑to‑Have

• MicroStrategy development familiarity (metrics/filters/prompts/roles) and performance tuning.
• Experience building KPI frameworks for work‑order management & field operations (e.g., SLA, MTTR, first‑time fix, travel distance, utilization).

Key Competencies

• Architecture Leadership: Defines reference patterns, enforces guardrails, and mentors analysts/technicians throughout delivery.
• Business Partnering: Translates operational needs into data models and dashboards aligned to three decision‑making profiles.
• Quality & Compliance: Builds robust validation and reconciliation processes; ensures functional validation and clean acceptance.
• Delivery Excellence: Proactive communication, risk/issue escalation, and cadence reporting mapped to the SOW schedule

Key Skills

Education

Bachelor's degree