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Job Description & How to Apply Below
If you are passionate about multi-cloud cost, usage, resource, and financial datasets, and love architecting clean, scalable analytical engines in Google Cloud (GCP) / Big Query, we want to hear from you.
Req.#The recruiting efforts for this position are intended to fill an existing vacancy for a new position.
Responsibilities Data Architecture & Modeling:
Define the target data architecture for multi-cloud cost, usage, resource, contract, financial, metadata, and operational datasets. Design conceptual, logical, and physical data models optimized for Big Query analytical workloads
Documentation & Governance:
Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions. Define clear ownership boundaries across raw, standardized, curated, and analytics-ready data layers
Semantic & Domain Modeling:
Establish canonical entities, domain models, semantic datasets, and reusable dimensions for traditional reporting as well as modern AI-agent use cases
Integration & Ingestion Design:
Design integration patterns for APIs, files, databases, event streams, and semi-structured enterprise data. Ensure data is properly mapped, normalized, and reconciledAI & Agent Readiness:
Partner with AI Engineers to design safe, discoverable, read-only Big Query datasets and MCP tools for agent access. Define query and schema standards that enable reliable agent reasoning, structured responses, analytics, and recommendations
Performance & Cost Optimization:
Review SQL queries, data pipelines, schemas, and integration designs for quality, scalability, maintainability, performance, and cost efficiency. Define Big Query best practices for partitioning, clustering, materialized views, and query optimization
Data Governance & Leadership:
Establish governance standards for lineage, ownership, access control, retention, data classification, quality, and freshness. Participate in architecture and code reviews, offering technical leadership across the data domain
Requirements
Experience:
Strong professional background in data engineering, data architecture, analytics engineering, or backend/data platform development
Data Modeling:
Deep expertise in conceptual, logical, physical, dimensional, canonical, and domain-oriented data modeling
Cloud Data Warehousing:
Advanced SQL skills and hands-on experience designing large-scale analytical datasets, data marts, and multi-source integration pipelines, specifically using Google Cloud Big Query (or similar cloud data warehouses)
GCP Ecosystem:
Strong GCP knowledge, including Big Query, Cloud Storage, IAM, service accounts, Pub/Sub, and GKE integration patterns
Mapping & Specifications:
Proven ability to produce source-to-target mappings, transformation specifications, data contracts, and lineage documentation
Performance Tuning:
Expertise in Big Query partitioning, clustering, performance tuning, and cost-efficient query design
Programming & Integration:
Hands-on Python experience for data services, Proofs of Concept (POCs), transformations, or API integrations.
Experience with REST APIs, event-driven integration, batch processing, and semi-structured data Governance & Security:
Strong understanding of data governance, data quality, reconciliation, schema evolution, and least-privilege access patterns
Collaboration & Review:
Experience conducting architecture reviews, mentoring engineers, and driving consensus across cross-functional technical teams
We offer
Extended Healthcare with Prescription Drugs, Dental and Vision, and Healthcare Spending Account (Company Paid)
Life and AD&D Insurance (Company Paid)
Employee Assistance Program (Company Paid)
Telehealth (Company Paid)
Short-term Disability (Company Paid)
Long-Term Disability Paid Time Off (including vacation and sick days)
Registered Retirement Savings Plan (RRSP) with Company match
Maternity/Parental/Adoption Leave Top-up Employee Stock Purchase Program Critical Illness Insurance Employee Discounts Unlimited access…
Position Requirements
10+ Years
work experience
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