Software Engineer – Data Engineering Platform (Python _ SQL _ PostGIS

Wood Mackenzie • Boston, MA

8h • Hybrid

About The Position

Wood Mackenzie is a global research, analytics and consultancy business serving the natural resources industry. We provide data, analytics and insights that help customers make informed decisions across oil, gas and LNG, power and renewables, chemicals, metals and mining. Our sector teams are located around the world and support customers with intelligence on assets, companies and market indicators. Together, we help customers address complex challenges and support the transition to a more sustainable future. LandGate, a Wood Mackenzie business, is a fast-growing vertical intelligence platform specialising in energy, infrastructure, and data centre site selection. Through proprietary datasets and market intelligence, it helps customers identify, evaluate, and develop energy and infrastructure opportunities across the United States.

The Software Engineer will join the team responsible for the core data platform supporting valuation and analytics products. The platform ingests, processes and maintains large-scale geospatial and energy datasets used across oil and gas, renewables, electrical infrastructure, carbon and land intelligence. This is a backend data engineering position focused on Python, PostgreSQL/PostGIS and Linux. The role will design, develop and maintain data pipelines, spatial data processes and data-quality controls that provide reliable information to downstream products and users. It is not primarily an application or front-end development role.

Requirements

• Practical software development experience using Python.
• Advanced working knowledge of PostgreSQL and SQL, including database design and query-performance optimisation.
• Experience using PostGIS or comparable geospatial database technologies.
• Experience building and maintaining ETL or data-engineering pipelines.
• Experience processing large or complex datasets.
• Experience implementing validation and data-quality controls.
• Working knowledge of Linux administration, scripting and automation.
• Effective analytical, diagnostic and problem-solving skills.
• Ability to communicate technical information clearly and work collaboratively across disciplines.

Nice To Haves

• Elasticsearch.
• AWS services, particularly Amazon S3.
• TypeScript, Node.js or REST API development.
• GIS formats such as Shapefile and GeoJSON.
• Spatial indexing or geospatial analytics.
• Data modelling, machine learning or statistical analysis.
• Energy, land, mineral rights, oil and gas, renewables, electrical-grid or carbon/CCUS datasets.

Responsibilities

• Design, develop, test and maintain Python-based ETL pipelines for large geospatial and energy datasets.
• Build and optimise PostgreSQL/PostGIS schemas, SQL queries and spatial data workflows.
• Develop automated processes for data ingestion, validation, transformation and promotion.
• Monitor data quality and investigate issues affecting the accuracy, completeness or reliability of data products.
• Maintain Linux-based data-processing environments, scheduled jobs and automation tooling.
• Support data engineering across energy infrastructure, land, oil and gas, renewables and carbon datasets.
• Collaborate with product, GIS and data science colleagues to understand requirements and deliver reliable data products.
• Diagnose pipeline, database and processing issues, implementing maintainable solutions.
• Contribute to documentation, engineering practices and the continuous improvement of data-platform processes.

Benefits

• We are a hybrid working company and the successful applicant will normally be expected to be physically present in the office at least two days per week to foster and contribute to a collaborative environment.
• Remote working arrangements will also be considered for this role, subject to the applicable approval process.
• Due to the global nature of the team, a degree of flexible working will be required to accommodate different time zones.
• Any out-of-hours collaboration should be planned proportionately and shared fairly across the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed