Finance Data Engineer (Senior Manager)

Accenture UK; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Accenture UK is seeking a Finance Data Engineer to own the finance data and ontology layer, building governed data products sourced from live ERP/EPM systems. You will design lineage, contracts and retrieval-ready services for AI, analytics and decision intelligence.

Responsibilities include building the finance ontology, pipelines from SAP/Oracle/Workday, and ensuring secure data lifecycle, with experience on Azure/AWS/GCP and Databricks/Snowflake. 10+ years preferred.

Qualifications

• Production data engineering experience with SQL, Python and modern data platforms.
• Hands-on ETL/ELT, data testing, Git and CI/CD practices.
• Experience with PySpark or dbt is beneficial.
• Knowledge of enterprise finance data structures and data contracts.

Responsibilities

• Build and extend the finance ontology and related data relationships.
• Engineer pipelines from SAP, Oracle, Workday and EPM into governed data products.
• Create entity-resolution and master/reference data capabilities across sources.
• Establish lineage, observability and data-quality checks for audit readiness.
• Define data contracts between delivery pods and client platforms.
• Collaborate with AI engineers on retrieval, grounding and provenance.

Skills

SQL

Python

Databricks

Snowflake

Fabric

ETL/ELT

Git

CI/CD

PySpark

dbt

Kubernetes

Education

Tools

Databricks

Snowflake

Palantir

Kubernetes

Job description

UKI Finance RP

Finance Data Engineer

The practice

Finance is one of the most demanding and valuable environments in which to apply modern technology. You will work with complex enterprise data, mission-critical processes and high-impact decisions, using AI, data and engineering to reshape how organisations plan, control performance and allocate resources. The opportunity goes beyond building technically strong solutions: you will see how those solutions influence cash, profitability, risk and business growth, and take them from experimentation into trusted, production-ready capabilities. Working in Finance Reinvention allows you to remain close to leading-edge technology while developing an understanding of the CFO agenda, gaining exposure to senior decision-makers and building the commercial judgement needed to solve enterprise-wide challenges. This combination of deep technical capability, finance-domain expertise and measurable business impact creates a differentiated career path that is difficult to develop in a purely technology-focused role.

Purpose of the role

Responsible for the finance data and ontology layer on which agentic solutions depend. Builds the entities, relationships, definitions, lineage and data contracts sourced from live ERP and EPM systems to a standard that supports controlled and auditable agent behaviour. The role owns governed finance data products, semantic models and retrieval-ready data services that are secure, permission-aware, observable and suitable for AI, analytics and decision intelligence.

Responsibilities

• Build and extend the finance ontology covering supplier, invoice, customer, receivable, journal, account, cost centre and forecast line, and the relationships between them, including controlled vocabularies, business glossaries, hierarchy history, ownership and lifecycle versioning.

• Engineer pipelines from SAP, Oracle, Workday and EPM platforms into governed data products, supporting structured and unstructured sources, batch and incremental ingestion, APIs, files and change-data-capture patterns as appropriate.

• Build entity-resolution and master or reference-data capabilities that reconcile identifiers, definitions and hierarchies across source systems and preserve source-to-target mappings.

• Establish lineage and evidence sufficient for audit, so that agent output can be traced to source, with automated data-quality checks, finance reconciliations, completeness and freshness measures, observability, alerts and recoverable operations.

• Define data contracts between delivery pods, and between Accenture delivery and client platform teams, including schemas, quality thresholds, access rules, service levels, versioning and change-control expectations.

• Experience deploying software or data products on Azure, AWS or GCP, DataBricks, Snowflake, Palantir etc using relevant cloud services and at least one of containers, Kubernetes or serverless patterns.

• Work with AI Engineers on retrieval and grounding, ensuring models receive appropriately scoped context, including chunking and embedding strategies, hybrid or graph retrieval, permission-aware filtering, provenance and retrieval evaluation.

• Implement security and privacy controls across the data lifecycle, including role- or attribute-based access, row or document-level permissions, masking or tokenisation, retention, tenant isolation and audit logging.

• Apply software and DataOps practices including Git, automated testing, CI/CD, infrastructure as code where relevant, performance tuning, cost optimisation and production support.

• Collaborate with finance SMEs, data owners, architects and governance teams to agree definitions, resolve data issues and embed sustainable stewardship and operating ownership.

• Data engineering

Essential experience

• Production data engineering, including SQL, Python, a modern data platform such as Databricks, Snowflake or Fabric, and orchestration tooling, with practical experience of ETL/ELT, data testing, Git and CI/CD; PySpark or dbt experience is beneficial.

• Working knowledge of finance data structures, including chart of accounts, entity hierarchy, sub-ledger to ledger relationships, intercompany and period close, together with actual, budget and forecast data, currencies, consolidation and management hierarchies.

• Strong data modelling discipline and the ability to justify and maintain definitional standards, including canonical or semantic models, data contracts, schema evolution, metadata, lineage and data-quality controls.

• Experience extracting and reconciling data from enterprise applications or complex operational systems using APIs, files, database interfaces or change-data-capture patterns.

• Experience deploying software or data products on Azure, AWS or GCP, DataBricks, Snowflake, Palantir etc. using relevant cloud services and at least one of containers, Kubernetes or serverless patterns. (AI engineer - desirable)

• Understanding of secure data engineering, including access control, encryption, secrets, privacy, retention and the handling of sensitive or regulated data.

• Ability to work with finance SMEs and technical teams to translate business definitions and controls into implementable data products and acceptance criteria.

• At least 10 years' relevant professional experience

Desirable

• Knowledge graph, semantic layer or ontology engineering experience, including technologies or standards such as Neo4j, RDF/OWL, SKOS, SPARQL or GraphRAG.

• Data quality, master data management or lineage tooling experience, including entity resolution, business glossaries, catalogues or platforms such as Collibra, Purview or Unity Catalog.

• Exposure to SOX or external audit requirements, GDPR, model-risk controls or regulated-data environments.

• Detailed knowledge of one or more finance-platform data models, such as SAP S/4HANA, Oracle Fusion, Workday Financials, Anaplan, OneStream or SAP Analytics Cloud.

• Experience evaluating retrieval quality for AI workloads, including embeddings, vector stores, hybrid search or reranking.

N/A

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360 value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.