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Accenture

Advises businesses and runs their technology

Finance Data Platform Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Typically 7 or more years delivering finance data platform work end to end.
  • Hands-on experience with one or more modern cloud data platforms, such as Snowflake, Databricks or Palantir Foundry.
  • Experience integrating data platforms with ERP estates such as SAP or Oracle and associated close, consolidation and reconciliation tooling.
  • Depth in enterprise structure, chart-of-accounts and master data design, on ERP programmes and platform builds, and in governance, lineage and data-quality controls for finance data models.
  • Experience with finance analytics and reporting, including semantic and metrics-layer design.
  • Exposure to AI-enabled solutions such as predictive forecasting and agentic use cases.
  • Familiarity with SQL, APIs and modern data-integration technologies, and some exposure to Python or machine learning platforms; deep engineering is not required.
  • Relevant cloud-data, platform or AI certifications, or a professional finance or accounting qualification.
  • Strong client-facing consulting capability, including explaining technical architecture decisions to mixed audiences in business terms.
  • Ability to lead multidisciplinary teams and work with controllers, senior data stakeholders and senior technology stakeholders.
  • Structured problem-solving and sound judgment in complex, ambiguous organizations.
  • Satisfactory BPSS and SC security clearance, requiring 5 years of continuous UK address history at application, typically with no periods of 30 consecutive days or more spent outside the UK.

Responsibilities

  • Design finance data platforms, including ingestion, conformed-core and curated-data layers, finance data products with ownership and quality expectations, and access, security and governance standards.
  • Lead selection and architecture decisions across Snowflake, Databricks, Palantir Foundry and comparable cloud data platforms, controlling platform cost and performance.
  • Design integrations between data platforms and client ERP estates and surrounding applications, including subledgers, general ledger, consolidation, close and reconciliation tools.
  • Set data pipeline designs using ETL, ELT and API patterns, and select scheduled batch, change-data capture or streaming approaches as appropriate.
  • Design for source-system conditions including changing master data, late postings, restatements and reopened periods; establish data-quality tests, monitoring and reconciliation to the ledger.
  • Design enterprise finance data structures, including chart of accounts, entities and ledgers, cost and profit-centre hierarchies, and underlying finance master data.
  • Design governance, ownership and lineage so reported figures trace to source transactions and the platform meets finance control and audit requirements.
  • Design reporting and analytics layers, including management reporting, self-service analytics, and semantic and metrics layers.
  • Enable performance analysis using governed platform data, including budget and forecast variance, driver analysis and profitability.
  • Help design AI models and agents for predictive forecasting, anomaly detection, AI-generated commentary and agentic workflows, with human-in-the-loop controls.
  • Direct data scientists and AI engineers building AI capabilities, and help clients move from isolated experiments to governed, explainable capabilities.
  • Lead client-facing design workstreams from discovery and architecture through deployment, adoption and hypercare.
  • Act as design authority for the finance data platform, ensuring it supports finance control, reconciliation and auditability; align senior finance, technology and data stakeholders through design reviews and trade-off discussions.
  • Contribute to design and deployment tasks, including reviewing data models, pipelines and reports.
  • Identify client needs and opportunities for follow-on work, build reusable assets and points of view, and develop people around the role.
  • Use agentic tools and orchestration in delivery while retaining human ownership of judgment and outcomes.

Desired Qualifications

  • Experience working with agentic tooling and orchestration in AI-first delivery.
  • Relevant cloud-data, platform or AI certifications, or a professional finance or accounting qualification.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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