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 using Python.
  • Expertise in PostgreSQL and SQL for database design and optimization.
  • Experience with PostGIS or similar geospatial database technologies.
  • Proficiency in building and maintaining ETL/data-engineering pipelines.
  • Experience processing large or complex datasets with data-quality controls.
  • Familiarity with Linux administration and automation scripting.
  • Strong analytical and problem-solving skills with effective communication abilities.

Responsibilities

  • Design, develop, and maintain Python-based ETL pipelines.
  • Build and optimize PostgreSQL/PostGIS schemas and spatial data workflows.
  • Create automated processes for data ingestion, validation, and transformation.
  • Monitor and investigate data quality issues affecting reliability.
  • Maintain Linux-based data processing environments and automate scheduled tasks.
  • Collaborate with cross-functional teams to deliver reliable data products.
  • Diagnose and implement solutions for pipeline and database issues.
  • Contribute to documentation and continuous improvement of data processes.

Benefits

  • Hybrid working arrangements with office presence recommended at least two days a week.
  • Flexible working hours to accommodate global team collaboration.
  • Encouragement for applicants who meet most essential criteria to apply.
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.

Werecognisethat experience can be gained indifferent 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.

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.

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