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

Wood Mackenzie

$110K — $130K *
Energy & Utilities
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of practical software development experience with Python.
  • Advanced expertise in PostgreSQL and SQL, especially in database design and performance optimization.
  • Experience with PostGIS or similar geospatial database systems.
  • Proven ability to build and maintain ETL or data-engineering pipelines.
  • Experience handling large and complex datasets, ensuring data integrity.
  • Knowledge of Linux administration and basic scripting for automation tasks.
  • Strong analytical, diagnostic, and problem-solving capabilities.

Responsibilities

  • Design and develop Python-based ETL pipelines for extensive geospatial and energy datasets.
  • Create and optimize PostgreSQL/PostGIS schemas and SQL queries.
  • Automate data ingestion, validation, transformation, and promotion processes.
  • Monitor data quality and address issues impacting the accuracy and reliability of data.
  • Maintain Linux environments for data processing and automation jobs.
  • Support data engineering efforts across various energy and geospatial domains.
  • Collaborate with cross-disciplinary teams to align on data product requirements.
  • Diagnose and resolve pipeline and database processing issues effectively.

Benefits

  • Hybrid working model with in-office collaboration at least two days a week.
  • Flexible work arrangements with remote work options considered.
  • Opportunity to work in a global team across different time zones.
  • Encouragement to apply even with partial experience related to essential qualifications.
Full Job Description
Role Purpose

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.

Main 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.

About You

Essential experience and capabilities
• 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.

Desirable experience
• 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.

We recognise that experience can be gained in different ways. If you meet most of the essential requirements and are interested in the role, we encourage you to apply.

Working Arrangements
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.

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