Job description

This is a hands-on delivery role that explicitly combines Technical Business Analysis and Engineering/Development. You will own outcomes end-to-end: partner with Liquidity Risk and Treasury stakeholders to shape requirements and controls, then personally work in the data and code (SQL/Python/Unix) to build, validate, and release solutions into production. What You’ll Deliver: You will lead and implement technology initiatives that support Liquidity Risk Management capabilities such as cash positioning, funding and maturity profiles, collateral/margin impacts, liquidity metrics, stress testing/scenario outputs, limits/threshold monitoring, and internal/regulatory-oriented reporting, with strong data lineage, controls, and auditability. Key Responsibilities: End-to-End Delivery & Stakeholder Leadership • Lead delivery of Liquidity Risk technology enhancements and new onboarding/integration initiatives across Liquidity Risk, Treasury/Funding, Finance, Operations, and IT. • Own the full lifecycle: requirements discovery → data mapping/lineage → solution design → build execution → testing/UAT → release planning → post-implementation validation. • Serve as the primary point of contact for scope, priorities, dependencies, and issue resolution; communicate status and risks clearly to senior stakeholders. • Contribute to delivery standards/best practices; mentor junior team members as needed. Hands-On Engineering: Data, Code, and Production Readiness • Develop and optimize advanced SQL to support liquidity metric calculations, exposure/aggregation views, reconciliations, controls, and drill-down diagnostics (joins, CTEs, window functions; performance tuning concepts). • Build Python tooling for data transformation, automation, monitoring/diagnostics, and analytical workflows (pandas/batch patterns preferred). • Use Unix/Linux and shell scripting to support batch processes, operational tooling, and production support diagnostics. • Perform root-cause analysis for data/metric/reporting breaks (mappings, identifiers, cutoffs/timing, model assumptions/inputs) and drive remediation to closure. Liquidity Data Enablement: Cash, Funding, Collateral & Flows • Analyze and validate core liquidity inputs including cash balances, settlement/payment flows, secured/unsecured funding, collateral movements, margin, and maturity profiles. • Define and implement mappings and controls from upstream sources (e.g., Treasury platforms, GL/subledger, payments, collateral/margin systems, market/security master where needed) to downstream consumers (liquidity risk engines, stress pipelines, dashboards, internal reporting). • Build reconciliations and exception monitoring for cash positions, funding balances, and flow projections, including completeness checks and end-of-day cutoff logic. Liquidity Metrics, Stress Testing & Reporting Traceability • Enhance analytics pipelines for metrics such as liquidity buffers, survival horizon, cash flow gap/laddering, concentration, encumbrance, funding mix, and stress/scenario impacts. • Support limit/threshold monitoring through drill-downs and roll forwards. • Ensure strong traceability: source balances/flows → transformations → liquidity metrics → reports, with audit-ready evidence and reproducibility. Documentation, Controls & SDLC Governance • Produce and maintain high-quality artifacts: business/functional requirements, technical specs, solution designs, data dictionaries/mappings, test plans, validation evidence, and release notes. • Manage user stories, defects, and delivery workflows in JIRA (Confluence preferred). • Define acceptance criteria; partner with QA/UAT to validate results and support sign-off under strong change control. Required Experience & Skills • 7+ years (VP-level) or 5+ years (senior consultant) in a Developer/BA hybrid, Technical BA, Risk IT Analyst, or engineering role with significant delivery ownership in financial services. • Demonstrated delivery into production systems involving risk/treasury/finance data and complex cross-team dependencies. Technical: • Advanced SQL on enterprise relational databases (e.g., Oracle/SQL Server/PostgreSQL): complex querying and tuning; strong reconciliation and data quality patterns. • Python for automation and analysis; ability to build pragmatic tooling that improves reliability and speed of investigation. • Unix/Linux command line and shell scripting; comfort supporting batch cycles, cutoffs, restarts, and operational diagnostics. • Strong understanding of data modeling and data lineage across multiple upstream/downstream systems. • SDLC discipline with JIRA; strong testing/UAT and release execution experience. Liquidity Risk / Treasury Domain: • Strong understanding of Liquidity Risk Management concepts and data, including: • cash positioning, currencies, legal entities, liquidity buffers funding sources/maturities, rollovers, concentration • cash flow forecasting/laddering, settlement/payment flows • collateral/margin/encumbrance impacts • stress testing/scenario analysis, limits and monitoring • Experience with liquidity risk systems, treasury platforms, or liquidity reporting frameworks strongly preferred. Education & Competencies • Bachelor’s degree in Computer Science, Business, Engineering, Finance, Data Science, or related discipline (or equivalent experience). • Systems integration experience: REST APIs (auth/error handling/pagination), file-based feeds (SFTP; CSV/JSON/XML), message-based patterns. • Git and CI/CD concepts; cloud/data platforms (AWS/Azure/GCP; Snowflake/data lake/warehouse concepts). • BI/reporting tools (Tableau, Power BI, SSRS). • Advanced Excel; MS Project (or similar planning tools). Primary Location Full Time Salary Range of $175,000 - $225,000.

Requirements

Must-haves

End-to-End Delivery & Stakeholder Leadership
Lead delivery of Liquidity Risk technology enhancements and new onboarding/integration initiatives across Liquidity Risk, Treasury/Funding, Finance, Operations, and IT.
Own the full lifecycle: requirements discovery → data mapping/lineage → solution design → build execution → testing/UAT → release planning → post-implementation validation.
Serve as the primary point of contact for scope, priorities, dependencies, and issue resolution; communicate status and risks clearly to senior stakeholders.
Contribute to delivery standards/best practices; mentor junior team members as needed.
Hands-On Engineering: Data, Code, and Production Readiness
Develop and optimize advanced SQL to support liquidity metric calculations, exposure/aggregation views, reconciliations, controls, and drill-down diagnostics (joins, CTEs, window functions; performance tuning concepts).
Use Unix/Linux and shell scripting to support batch processes, operational tooling, and production support diagnostics.
Perform root-cause analysis for data/metric/reporting breaks (mappings, identifiers, cutoffs/timing, model assumptions/inputs) and drive remediation to closure.
Liquidity Data Enablement: Cash, Funding, Collateral & Flows
Analyze and validate core liquidity inputs including cash balances, settlement/payment flows, secured/unsecured funding, collateral movements, margin, and maturity profiles.
Build reconciliations and exception monitoring for cash positions, funding balances, and flow projections, including completeness checks and end-of-day cutoff logic.
Liquidity Metrics, Stress Testing & Reporting Traceability
Enhance analytics pipelines for metrics such as liquidity buffers, survival horizon, cash flow gap/laddering, concentration, encumbrance, funding mix, and stress/scenario impacts.
Support limit/threshold monitoring through drill-downs and roll forwards.
Ensure strong traceability: source balances/flows → transformations → liquidity metrics → reports, with audit-ready evidence and reproducibility.
Documentation, Controls & SDLC Governance
Produce and maintain high-quality artifacts: business/functional requirements, technical specs, solution designs, data dictionaries/mappings, test plans, validation evidence, and release notes.
Define acceptance criteria; partner with QA/UAT to validate results and support sign-off under strong change control.
Required Experience & Skills
7+ years (VP-level) or 5+ years (senior consultant) in a Developer/BA hybrid, Technical BA, Risk IT Analyst, or engineering role with significant delivery ownership in financial services.

Nice-to-haves

Build Python tooling for data transformation, automation, monitoring/diagnostics, and analytical workflows (pandas/batch patterns preferred).
Manage user stories, defects, and delivery workflows in JIRA (Confluence preferred).
Experience with liquidity risk systems, treasury platforms, or liquidity reporting frameworks strongly preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonjirarestci/cdawsazuregcp

Platform: oracle-cloud
Effort: medium