Banking Data Analyst / Techno-Functional BA Engagement 6-week fixed-scope consulting engagement (Phase 1 Data Platform) Time commitment ~80 hours total; ~13 hrs/wk average, including the data-quality window Location Remote-first, with on-site sessions in Chambersburg, PA at stage boundaries as needed Start Name confirmed before kickoff About the Role A Pennsylvania community bank (~300 employees, ~80,000 accounts) is assessing its data foundation ahead of AI use cases such as a Relationship Manager Copilot, Customer 360, and automated underwriting. This combined analyst and business analyst role is the engagement's day-to-day engine. You gather requirements from commercial lending, retail, and trust, profile the data behind the first use case, and keep a clean written record of every decision. You work alongside the Lead Data Architect and the bank's own data and analytics team.
This is an assess-and-design engagement. It is read-only and sample-based, with no cleansing, remediation, or production changes. Responsibilities Business discovery and requirements
Plan and facilitate one combined working session across commercial lending, retail, and trust to capture what a Customer 360 view must answer, current cross-sell blind spots, and underwriting data needs.
Document outcomes as a use-case and key requirements log that feeds the architecture and Phase 2 plan.
Send agendas and pre-reads three business days ahead and confirm attendees so the bank's time is protected.
Issue outcomes, decisions, and actions within 24 hours of every session into a running decision log. Where recording is not permitted, your minutes serve as the formal record.
Data-quality assessment
Confirm ~30 Critical Data Elements (CDEs) with the bank, and map each to every system where it lives.
Profile completeness, validity, consistency, duplication, and cross-system consistency for each CDE, using stated sample sizes and confidence levels.
Flag any CDE that could act as a fair-lending proxy so later governance work starts from a known list.
Size the remediation backlog and ETL and vector-ETL effort at order of magnitude, ranked by which first-use-case prerequisites each issue blocks.
Review everything outside the CDE footprint, including three loan origination systems, at inventory and interface level.
Current-state baseline
Build the source inventory (owner, domain, location, volumes, interfaces) from the bank's artifacts, and baseline the existing AI footprint such as fraud, AML, and BSA summarization.
Support the maturity scorecard by gathering and organizing the evidence behind each score.
Governance and Phase 2 support
Support the Lead Data Architect on the governance framework, stewardship model, and Phase 2 plan inputs.
Work side by side with the bank's Salesforce-strong analysts so the team picks up profiling and documentation practice during the engagement.
Required Qualifications
6+ years as a data analyst, business analyst, or techno-functional BA, with at least 3 years in banking or financial services.
Strong hands-on SQL, and experience profiling data for completeness, validity, consistency, and duplication with a profiling tool or in code.
Working knowledge of banking data domains: customer and account, deposits, commercial and retail lending, loan origination, and trust or wealth.
Experience facilitating cross-functional requirements sessions and writing clear requirements, use cases, and decision logs.
Familiarity with CRM data, ideally Salesforce Financial Services Cloud, and with how data moves between core, CRM, and origination systems.
Strong written communication. Able to produce minutes and structured findings within 24 hours.
Comfortable working inside a small client team and a compressed six-week schedule.
Preferred Qualifications
Community bank experience, and exposure to FIS core banking or trust platforms such as InfoBanc.
Experience with Critical Data Element programs, data lineage, or data governance and stewardship.
Knowledge of fair-lending concepts and proxy variables, and of regulatory data expectations such as BSA/AML.
Exposure to MuleSoft or other integration tooling, and to Snowflake, Databricks, or SQL Server environments.
Familiarity with entity resolution, Customer 360 projects, or AI and LLM data prerequisites.
CBAP, CDMP, or comparable certification.
Engagement Requirements
Passes vendor onboarding before kickoff: security and vendor-risk review, background check, NDA, and insurance certificates.
Works on a client-imaged laptop with profiling tools, VPN, and MFA, using named read-only credentials. Follows the client's data-handling rules on sampling limits, PII masking, and on-device-only work.
U.S.-based and onshore-only access may be required by the client's policy.

Banking Data Analyst / Techno-Functional BA

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