Senior Business Analyst – contract role Urgent Need

Role: Senior Business Analyst

Location: Alpharetta, GA 

Duration: 6 months contract

 

Should be expert in Banking domain and data skills

 

 

Position Overview

We are seeking a Senior Business Analyst with hands-on banking domain experience to serve as the bridge between banking stakeholders and data, analytics, and engineering teams. The successful candidate will understand how retail and commercial banks operate, ask informed questions, challenge assumptions constructively, and convert business objectives into clear data requirements and measurable outcomes.

This role requires a consultative professional who can contribute banking context from the start, facilitate executive and subject-matter-expert conversations, and help shape data products that support reporting, Customer 360, profitability, growth, customer experience, and risk-related decisions.

 

Key Responsibilities

Banking Domain Consulting

Lead discovery sessions and workshops with executives, business leaders, product owners, operations teams, and subject-matter experts.

Bring practical knowledge of retail and commercial banking products, processes, customer journeys, and performance measures.

Frame the right business questions, identify gaps, and understand recommended relevant KPIs, analytical use cases, and decision-support opportunities.

Provide informed starting points based on banking practices while adapting definitions and measures to the bank’s specific policies and operating model.

Help stakeholders prioritize initiatives according to business value, feasibility, data readiness, and risk.

Data & Analytics Translation

Define business requirements for data lakes, lakehouses, data warehouses, Customer 360, business intelligence, and advanced analytics initiatives.

Translate business questions into data requirements, source-to-target needs, business rules, calculations, and acceptance criteria.

Partner with data architects, data engineers, BI developers, and data scientists to create trusted, business-ready datasets and semantic models.

Define and govern KPI formulas, dimensional definitions, data-quality rules, reconciliation logic, and reporting standards.

Validate that data models support dashboards, Salesforce and CRM use cases, analytics, and future AI-driven capabilities. 

 

Required Qualifications

12+ years of business analysis, product ownership, business consulting, or related experience.

5+ years of direct experience supporting banks or banking business units in the United States.

Demonstrated experience on data, analytics, reporting, data warehouse, lakehouse, Customer 360, or comparable banking transformation initiatives.

Ability to discuss banking measures and data concepts without requiring the client to explain foundational industry terminology.

Proven experience leading stakeholder workshops and translating complex business needs into clear requirements for technical teams.

Strong written and verbal communication skills, including executive-level presentation and facilitation capability.

Working knowledge of Agile delivery, requirements management, user acceptance testing, and change control.

 

Preferred Qualifications

Experience with regional or mid-sized US banks, particularly institutions with approximately $5B to $20B in assets.

Experience across two or more recent banking data initiatives with comparable product and operating complexity.

Exposure to Microsoft Fabric, Azure data services, Power BI, SQL, Salesforce, data governance, or metadata management.

Experience defining measures for deposits, customer and product profitability, lending, relationship management, churn, cross-sell, or executive reporting.

CBAP, PMI-PBA, CSPO, data or analytics certification, or relevant banking qualification.

 

Key Competencies 

Consultative mindset: Brings hypotheses, options, benchmarks, and recommendations rather than waiting for detailed instructions. 

Banking fluency: Understands products, measures, operational context, and the language used by bank stakeholders. 

Data literacy: Connects business questions to source data, transformations, quality controls, curated models, and consumable insights. 

Analytical judgement: Distinguishes useful measures from misleading ones and tests whether definitions support the intended decision. 

Stakeholder leadership: Builds credibility with executives and SMEs while maintaining alignment with technical delivery teams. 

Outcome orientation: Keeps requirements linked to revenue growth, cost reduction, loss reduction, risk reduction, or customer experience.