Business Analytics Manager at PNC managing email marketing campaigns and leading analytics initiatives. Collaborating across teams to optimize engagement and deliverability while ensuring compliance in marketing.
About the role
- Senior Data Analyst delivering enterprise-wide data foundations in a complex banking environment. Providing hands-on analysis and data architecture input to improve data structure and trust.
Responsibilities
- Designing and evolving conceptual and logical data models across core banking domains.
- Performing hands-on SQL analysis to profile datasets, validate definitions, reconcile discrepancies, and identify gaps.
- Providing modelling-aligned architecture inputs (conformed entities, keys, reference/master data approach, integration patterns, semantic layer considerations).
- Driving standardisation of data definitions and produce practical artefacts (data dictionary/glossary, mappings, documentation).
- Partnering with delivery teams to support metadata, lineage, and governance-aligned documentation, and ensure modelling decisions are adopted.
Requirements
- What we need you to have:
- 5–10+ years in hands-on data analysis and/or data modelling, ideally in banking/financial services.
- Strong conceptual/logical modelling capability and ability to translate business needs into implementable structures.
- Strong SQL and confidence working directly with complex datasets.
- Strong stakeholder engagement and clear communication/documentation skills.
- Enterprise data modelling (banking-grade): can structure domains end-to-end (customer/account/product/transaction etc.) with clear keys, relationships, and definitions.
- Hands-on data analyst mindset: strong SQL + profiling/reconciliation; comfortable working directly with messy real-world bank data to prove what’s true.
- Data architecture awareness: can design models that land well in a lakehouse (layering, conformed entities, semantic alignment) and work across relational + semi/unstructured data.
- Delivery + stakeholder execution: can run working sessions, drive decisions, produce usable artefacts (dictionary/glossary/mappings) and keep momentum with platform/engineering teams
- What we'd like you to have:
- Forward-thinking modelling: exposure to AI/GenAI-assisted modelling/discovery (automation of documentation/metadata, semantic modelling concepts, knowledge-graph thinking).
- Data quality & observability orientation: experience defining critical elements, data quality checks/metrics, and supporting “data contracts”/early issue detection patterns.
- Lakehouse + enterprise BI/semantic familiarity: understands how models support analytics/MIS-style consumption and tool rationalisation decisions.
- Consulting background (nice signal): Big 4 / Accenture / Capgemini or similar (optional, not required).
Benefits
- **Benefits & Growth Opportunities:**
- · Competitive salary and performance bonuses
- · Comprehensive health insurance
- · Professional development and certification support
- · Opportunity to work on cutting-edge AI projects
- · Flexible working arrangements
- · Career advancement opportunities in a rapidly growing AI company
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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