What You'll Do
We're hiring a Senior Data Architect to lead the Finance Data Hubdesigning the blueprint and standards for finance data assets across Snowflake, ADF, and Power BI. You'll operationalize our data mesh with a medallion lakehouse, deliver robust semantic models for Commercial Analytics, Core Finanance (AP/AR/GL/FA), support a breadth of partnering data domains across Eaton, and embed governance and SOXready controls so Finance can trust, scale, and automate decisions.
- Own the end to end data architecture roadmap for our Snowflake centric Finance Data Hub and medallion/lakehouse patternsaligning enterprise (bronze/silver) and domain (gold) layers for scale, reuse, and velocity.
- Design and govern the semantic layer (enterprise curated datasets, star schemas, RLS) that delivers a single version of truth for analytics in Power BI; codify standards and deployment practices.
- Assess application/data platform architecture choices: decide sourcing patterns, security rules (RBAC/RLS), privacy constraints, and data residency controls in partnership with platform/security teams.
- Establish repeatable ingestion & transformation patterns with Azure Data Factory and Snowflake (orchestration, environments, naming, CI/CD), and champion DataOps guardrails.
- Assess high level data architecture from context: translate objectives into conceptual entities (e.g., customer invoices, customer master, finance master data like site and accounts) and drive a fit for purpose target state.
- Advance federated data governance and quality with domain owners and stewardsCDE identification, DQ rules, scorecards, lineage, and catalog practices that drive trust.
- Raise our AI data readinessensure data products include the metadata, quality, lineage, and controls AI requires; align with emerging AI governance and risk processes.
- Engineer for performance, reliability, and costoptimize Snowflake warehouses, refresh/gateway health, and observability for >99% availability across the analytics estate.
- Embed security and compliance by designRBAC/RLS, encryption, least privilege, and cloud security controls across data stores, pipelines, and BI surface.
- Coach and uplift talentmentor architects, engineers, and stewards; cultivate reusable patterns, reference implementations, and strong data as an asset practices.
- Operationalize CI/CD for data & BIgovern branching, releases, and deployment pipelines for Snowflake/Power BI; drive automated reconciliation and validation.
- Partner across platform & analytics teams to harmonize ingestion/lakehouse with reporting and ML, accelerating domain roadmaps and cross domain reuse.
- Co create test strategy and exit criteria with the Product Owner; define data/semantic validation and performance thresholds needed for release and sign off.
- Joint design sign off: partner with DF&I techno functional leadership to review and sign off the detailed technical design and data model for FDH assets.
Qualifications
Bachelor's in Computer Science, Data/Information Systems, Engineering, Mathematics, or related field (or equivalent experience).
810 years in data architecture/engineering with a record of shipping financegrade data assets and semantic models.
5+ years dimensional modeling and ELT/ETL for analytical workloads; 3+ years handson with Snowflake, ADF, and Power BI at enterprise scale.
Skills
- Architectures & Patterns: Data mesh (domain ownership, federated governance) and medallion lakehouse (bronze/silver/gold) applied to Finance use cases.
- Snowflake (Finance focus): warehouse optimization, materialized views/search optimization, secure data sharing, and workload segregation for close windows.
- ADF & DataOps: standardized pipelines, environment promotion, CI/CD options for data; defensible naming and metadata capture for auditability.
- Semantic Layer & BI: Power BI deployment pipelines, DAX standards, Tabular Editor/DAX Studio usage, and scalable RLS patterns for sensitive finance hierarchies.
- Modeling Standards: domain agnostic bronze/silver guidance and domain aligned finance gold (facts/dims for AP, AR, GL, FA, Intercompany); conformed dimensions and metric definitions.
- Governance & MDM: CDE identification, glossary/lineage, DQ rules & scorecards; integration with finance hierarchies/MDM and stewardship councils.
- Security/Compliance: RBAC, RLS, encryption and Azure security controls; awareness of SOX and data privacy impacts on finance reporting pipelines.
- Testing & Readiness: automated reconciliation SnowflakePower BI, SIT/UAT for KPI sign off, and performance testing for semantic models.
- AI Data Readiness & Governance: AI risk checkpoints, data policy as code direction, and regulatory awareness embedded in asset lifecycle.
- Businessanchored architecture: connects highlevel finance outcomes (e.g., DSO reduction) to conceptual data models and target state architectures (invoices, customer master, finance master data).
- Standards stewardship: demonstrated ability to apply and contribute to enterprise data mesh standards/playbooks, surfacing reusable patterns and guardrails.
- Finance domain fluency communicates trade offs in plain language; aligns stakeholders around close timelines, reconciliations, and metric definitions.
- Systems & lifecycle thinking connects ingestionmodelingsemanticconsumption with documentation and enablement that auditors and analyst's trust.
- Leadership & influence: mentors engineers/stewards; builds consensus across Finance, Platform, and Governance forums.
- Outcome orientation: delivers measurable gains in reliability, quality, adoption, and cost within FDH.
- Collaborative orchestration: not the expert in every domain, but consistently brings the right people together (DF&I product owner, Architecture Guild, IDM Finance BU team, platform/security, stewards) to move from intent design sign off release.
