Market risk engineering developer Work, Jobs in Dunfermline (with Salaries)

VP Data Engineering
Wood Mackenzie Limited —Edinburgh
- AWS
- Machine learning
- AI
Quick apply
Technical Director - Civil Engineering (Development)
WSP —Edinburgh
- Part-time
- Hybrid work
- Business development
- Presentation skills
- Team management
- Flexitime
- Work from home
Co-Managing Director – UK & Ireland
BayWa r.e. —Edinburgh
- Full-time
- Management
- Engineering
- English
- Employee assistance programme
Engineering Lead - Civils & Construction
Xodus Group —Edinburgh
- Full-time
- Hybrid work
- Civil engineering
- Bachelor's degree
- Construction
- Employee assistance programme
- Life insurance
Quick apply
Associate
BlackRock Investments —Edinburgh
- Full-time
- Hybrid work
- Computer Science
- Engineering
- Java
- Work from home
Solution Architect
Computershare —Edinburgh
- Full-time
- Hybrid work
- APIs
- Work from home
Quality Engineer
Aberdeen —Edinburgh
- Full-time
- Hybrid work
- Azure
- JavaScript
- APIs
- Annual leave
- Employee discount
9d
Development Team Lead
Dayshape —Edinburgh
- £67,000 - £80,000 a year
- Full-time
- Hybrid work
- Azure
- Management
- JavaScript
- Employee assistance programme
Quick apply
20h
Senior/Associate Fire Engineer – Expert Witness
Jensen Hughes —Edinburgh
- Engineering
- Continuous improvement
- Communication skills
- Annual leave
- Employee assistance programme
Principal Flood Modeller
Civic —Edinburgh
- Full-time
- Hybrid work
- Engineering
- Analysis skills
- Supervising experience
- Annual leave
- Employee assistance programme
Quick apply

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market risk engineering developer jobs near dunfermline

VP Data Engineering

Wood Mackenzie Limited -
Edinburgh

Quick apply

Job details

Qualifications

Cost management
Data modelling
Cloud architecture
Spark
AWS
Machine learning
S3
Redshift
AI
Leadership
Communication skills
Graph databases

Full job description

Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape.

For over 50 years our work has guided the decisions of the world’s most influential energy producers, utilities companies, financial institutions and governments.

Now, with the world’s energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That’s why we’ve redefined what’s possible with Intelligence Connected.

By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe.

This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence – whether planning days, weeks, months or decades ahead.

Wood Mackenzie
Intelligence Connected

WoodMac.com

Wood Mackenzie Brand Video

Wood Mackenzie Values

Inclusive – we succeed together
Trusting – we choose to trust each other
Customer committed – we put customers at the heart of our decisions
Future Focused – we accelerate change
Curious – we turn knowledge into action

Role Summary

The Vice President of Data Engineering is responsible for defining, building, and scaling a modern, enterprise-wide data engineering capability within a federated operating model. This role will lead the design and delivery of robust, secure, and high-performing data pipelines, with a strong focus on AWS-native architectures and Snowflake-based data warehousing.

The VP of Data Engineering will establish best-in-class engineering practices, enabling domain-oriented data ownership while ensuring consistency through shared standards, governance, and platform capabilities. A critical aspect of the role is enabling the development of AI-ready data ecosystems, including knowledge graphs, ontologies, and semantically enriched datasets that support advanced analytics, machine learning, and AI-native applications.

Role Responsibilities

Define and execute the enterprise data engineering strategy aligned to a federated (data mesh-style) operating model, balancing domain autonomy with centralized governance

Build, scale and lead a high-performing data engineering organization, including platform, enablement, and domain-aligned teams

Architect and oversee scalable, secure data platforms leveraging AWS services (e.g. S3, Glue, Lambda, EMR, Redshift), dbt and Snowflake

Establish best practices for data ingestion, transformation, orchestration, and serving (batch, streaming, and real-time patterns)

Drive adoption of modern data engineering principles including DataOps, CI/CD, infrastructure-as-code, and automated testing frameworks

Define and enforce data governance standards, including data quality, lineage, cataloging, security, and compliance across federated domains

Enable self-service data capabilities through reusable data products, shared tooling, and developer platforms

Lead the design and implementation of AI-native data architectures, including feature stores, vector databases, and semantic layers

Champion the creation and integration of knowledge graphs and ontologies to enhance data discoverability, interoperability, and contextual understanding

Collaborate with senior stakeholders across engineering, product, analytics, and AI/ML teams to deliver business value through data

Key Skills and Experience

Proven experience leading large-scale data engineering organizations in complex, federated or matrixed environments

Deep expertise in AWS data ecosystem (S3, Glue, Lambda, Kinesis, EMR, IAM, Lake Formation) and cloud-native architecture patterns

Strong hands-on and architectural experience with Snowflake/dbt/Airflow, including performance optimization, data modelling, and cost management

Expertise in building scalable modern data platforms (data lakes, lakehouses, and data warehouses) enabling reliable real-time and batch analytics

Strong understanding of distributed data processing frameworks (e.g. Spark, Flink) and streaming technologies

Demonstrated implementation of DataOps practices, including CI/CD pipelines, observability, testing, and automated deployments

Experience designing and operationalizing data governance frameworks in a federated or data mesh environment with self-service and trusted data capabilities

Highly versed in delivering ML/AI-ready ecosystems (feature stores, semantic layers, graph databases) aligned with executive stakeholders to drive business impact

Practical experience with knowledge graphs, ontologies, semantic modelling (e.g. RDF, OWL), delivering faster insights

Strong leadership, stakeholder management, and communication skills, with the ability to influence at executive level and drive organizational change.

Equal Opportunities

We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov

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Refine Your Search

market risk engineering developer jobs in dunfermline

VP Data Engineering

Technical Director - Civil Engineering (Development)

Co-Managing Director – UK & Ireland

Engineering Lead - Civils & Construction

Associate

Solution Architect

Quality Engineer

Development Team Lead

Senior/Associate Fire Engineer – Expert Witness

Principal Flood Modeller

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