Power BI Architect

Function Cloud & Data Engineering

We're Hitachi Digital Services, a global digital solutions and transformation business with a bold vision of our world's potential. We're people-centric and here to power good. Every day, we future‑prove urban spaces, conserve natural resources, protect rainforests, and save lives. This is a world where innovation, technology, and deep expertise come together to take our company and customers from what's now to what's next.

We make it happen through the power of acceleration.

Imagine the sheer breadth of talent it takes to bring a better tomorrow closer to today. We don't expect you to "fit" every requirement – your life experience, character, perspective, and passion for achieving great things in the world are equally as important to us.

• Masters in PowerBI, Finance Solution Data Architect with deep expertise in Supply Chain data and its intersection with Finance (Procure-to-Pay, Inventory Accounting, Costing, Cap Ex/OpEx, Vendor Spend Analytics).
• The architect will lead the design of scalable data solutions that unify supply chain and finance data across ERP, procurement, logistics, inventory, and billing systems‑enabling accurate reporting, forecasting, compliance, and operational insights.
• Own end‑to‑end data architecture for finance + supply chain analytics, reporting, and operational use‑cases.
• Define target‑state architecture (lake house/warehouse, streaming, APIs, metadata) aligned to enterprise standards.
• Design robust data ingestion and integration patterns (batch/stream, CDC, API‑based, file‑based).
• Ensure architecture supports auditability, reconciliation, and financial controls (traceability from source to report).
• Architect domain‑aligned datasets for:
  • Procure-to-Pay (P2P): requisitions, purchase orders, invoices, payments
  • Inventory & Warehousing: receipts, transfers, adjustments, stock valuation
  • Costing: standard/actual costing, landed cost, freight, BOM where relevant
  • Vendor & Spend: vendor master, contracts, pricing, spend categorization
  • Logistics: shipment tracking, carrier costs, delivery performance
• Enable integration between supply chain events and finance outcomes (e.g., GR/IR, accruals, capitalization, write‑offs).
• Create and maintain conceptual, logical, and physical data models (3NF, dimensional, Data Vault as applicable).
• Define canonical models and enterprise semantic layers for KPI consistency.
• Establish best practices for: master data (vendors, materials/items, locations, cost centers), reference data (currency, UOM, fiscal calendar, shipping terms), hierarchies (product, supplier, org, region).
• Partner with data engineering teams to implement ETL/ELT pipelines, orchestration, CI/CD, environment management.
• Performance tuning, partitioning, indexing, clustering strategies.
• Observability (logging, monitoring, SLA/SLI, cost optimization).
• Enable governed self‑service analytics through reusable datasets and thin‑report architecture.

• 10+ years in data/solution architecture with strong ownership of enterprise‑scale implementations.
• Strong experience designing data warehouses/lake houses, enterprise integration, and analytics platforms.
• Strong in data modeling (dimensional + normalized) and semantic layer design.
• Strong understanding of business processes and data: commercial operations, logistics, procurement, inventory, costing, vendor management.
• Cloud & Data Tech Stack:
  • Cloud:
    Azure
  • Data platforms:
    Fabric / Synapse
  • Data integration:
    Informatica / ADF / Fivetran / dbt / Airflow
  • Storage & formats:
    Parquet/Delta/Iceberg; S3/ADLS/GCS
  • Querying: advanced SQL; performance tuning; data partition strategies
  • Data governance:
    Collibra / Purview / Alation (or equivalent)
• BI/Analytics:
  Power BI (data modeling, DAX, performance tuning, semantic layer design, governance, deployment pipelines).
• Hands‑on experience with modern cloud data platforms and analytics.
• Design semantic models in Power BI for enterprise‑wide reuse, ensuring consistent KPI definitions.
• Hands‑on experience in DAX optimization, performance tuning, composite models, and security (RLS/OLS).
• Implement workspace architecture, deployment pipelines, and…