Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology. Enriched by human intelligence. In an ever-changing world, companies and governments need reliable and actionable insight to lead the transition to a sustainable future. That’s why we cover the entire supply chain with unparalleled breadth and depth, backed by over 50 years’ experience. Our team of over 2,400 experts, operating across 30 global locations, are enabling customers’ decisions through real-time analytics, consultancy, events and thought leadership. Together, we deliver the insight they need to separate risk from opportunity and make confident decisions when it matters most.
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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
We're seeking a talented Senior Software Engineer to join our Avatar team. This dynamic group plays a crucial role in bringing our industry-leading data and cutting-edge data science models to our internal customers, enabling them to deliver exceptional value.
Role Overview
We're looking for a Senior Software Engineer, Data Science Infrastructure & Optimization, to join our team! This is a critical technical role where you'll build and scale high-performance data infrastructure that powers our data science and modelling capabilities. You'll own the entire data lifecycle for modelling—from ingestion and transformation to automated scheduling—working with large-scale environmental datasets (like historical and forecasted weather data) that serve our entire organization. You'll enable seamless cross-functional data exchange, collaborate with engineering teams to ensure data flows in the right formats, and create self-service tools that empower data scientists to focus on what they do best: analysis and insights.
What You'll Do
1. Data Ingestion, Transformation, Delivery & Maintenance (35%)
Own and continuously improve data ingestion and transformation pipelines for large-scale climate and renewables datasets (weather data, renewable generation data), ensuring quality and timely delivery across the business
Facilitate cross-functional data exchange by ingesting and transforming datasets from other engineering teams and delivering them to stakeholders in their required formats
Build and deploy self-service infrastructure components (AWS Lambda functions, Glue/Athena tables, computing infrastructure) that make data access and preparation seamless for data scientists
Govern and manage large datasets across AWS environments, including data versioning and resolving quality issues for internal users
2. High-Performance Engineering & Code Acceleration (35%)
Design and implement optimization strategies for large-scale data processing and complex modeling tasks, leveraging parallelization and distributed computing tools like Dask for maximum performance and efficiency
Partner with data scientists to develop new code and scripts, refactoring them into maintainable, efficient, and reusable functions that prevent future bottlenecks
Create shared code frameworks, templates, and internal libraries that enforce best practices, contribute to company-wide tooling, and accelerate data science workflows
3. Data Quality, Testing & Standards (20%)
Define and implement comprehensive data quality assurance processes, including validity checks and proactive diagnosis and resolution of production issues
Build and maintain robust unit and BDD (Behave) test suites that validate complex transformation and modeling logic
Mentor data scientists on code structure, effective testing practices, and engineering standards
4. Architectural Leadership & Collaboration (10%)
Work closely with internal teams and end-users to understand their needs, address technical challenges, and co-design scalable architectural solutions that serve the broader organization
What You'll Bring
Experience in Data Engineering or software engineering supporting data science or research teams
Advanced Python proficiency and expert-level experience with distributed computing frameworks (e.g., PySpark, Dask)
Strong hands-on experience with AWS services for data processing (Step Functions, Lambda, Batch, S3, Athena)
Deep knowledge of software engineering best practices, including design patterns, refactoring, infrastructure as code, containerization, and CI/CD pipelines
Proven experience writing comprehensive test suites (unit, integration, and behavioural/Behave tests)
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
If you are applying for a role and have a physical or mental disability, we will support you with your application or through the hiring process.
