Senior Geospatial Analytics Engineer

4 weeks ago

Nairobi, Nairobi Area, Kenya M-Gas Full time

M-Gas is using technology to transform lives by providing clean cooking gas to all Kenyans 24 hrs, 7 days a week.

We give you our cylinder filled with gas, a smart meter, a gas cooker and a key card as part of our package so you don't have to pay the high upfront fee of buying a gas cylinder and cooker.

About the Job
Engage in the end-to-end geospatial analytics process, from data collection and manipulation to analysis and modeling.

Collaborate closely with the Technology teams to ensure seamless integration and alignment of geospatial analytics solutions with the company's data infrastructure.

Duties & Responsibilities

Spatial Data Processing:
Develop algorithms and scripts, utilizing SQL and Python, for processing and analyzing geospatial data. Implement spatial analytics techniques to derive meaningful insights.

Data Acquisition and Integration:
Identify and acquire relevant geospatial datasets, developing efficient processes for integration into our systems.

Data Quality Management:

Take charge of cleaning, transforming, and modeling geospatial data to enhance its accuracy, quality, and utility for business operations.


Data Visualization:
Collaborate to create visually compelling maps and geospatial visualizations, developing tools for interactive data exploration.

Spatial Data Modelling:

Fluent in tools for manipulating and visualizing both vector and raster data, with good awareness of other spatial analysis and modeling tools.

Cross-functional Engagement: Collaborate with technical teams, including Data Analytics, and business stakeholders to ensure geospatial analytics solutions meet business needs and drive value.


Data Governance:
Ensure all geospatial analytics solutions adhere to data security, privacy standards, and compliance requirements, safeguarding company geospatial data.

Innovative Geospatial Solutions Development:
Innovate and implement new methodologies in geospatial data analytics, keeping Circle Gas at the forefront of industry trends.

Geospatial Data Analytics Expertise:
Good content knowledge of geospatial data analysis. Examples (not exhaustive) could be remote sensing, routing/spatial network analysis, OpenStreetMap, Census/demographic data, parcel/assessor/address data etc.

Spatial Tools Mastery:

Expertise in utilizing spatial tools such as ArcGIS, QGIS, and other relevant geospatial software to manipulate and analyse geospatial data effectively.


Technical and Analytical Mastery:
Expertise working in SQL databases, Python environments and geospatial tools. Apply statistical analysis and machine learning for insightful geospatial interpretation.

Cross-Domain Communication:
Exceptional at articulating complex geospatial insights to stakeholders, facilitating clear understanding across geospatial engineering, analysis, and technology fields.

Innovative Problem-Solving:
Translate complex geospatial challenges into practical solutions, leveraging geospatial engineering techniques.

Interdisciplinary Collaboration:

Proven ability to work seamlessly with Data Analytics teams, GIS analysts, data scientists, and data engineers, fostering a collaborative environment.


Database and Infrastructure Knowledge:

Understanding of database technologies (e.g., Amazon Aurora, MongoDB, DynamoDB, SQL Server, MySQL, PostgreSQL) and engineering practices to manage and manipulate data effectively.

Requirements
Personal Attributes

Geospatial Data Analytics Expertise:
Demonstrate a minimum of 5 years of experience across geospatial analytics, engineering, and science. Proven ability to lead projects leveraging geospatial data for significant business impacts.

Cartography Proficiency:
Extensive experience in cartography, showcasing the ability to create visually compelling and informative maps. Familiarity with cartographic design principles to effectively communicate spatial insights.

Spatial Tools Mastery:

Expertise in utilizing spatial tools such as ARCGIS, QGIS, and other relevant geospatial software to manipulate and analyse geospatial data effectively.


SQL and Python Mastery:

Demonstrated proficiency in SQL and Python, utilizing these languages to manipulate and analyse geospatial data, and automate analytical processes.

Academic Qualifications
Qualification Name Level

Master's degree in Geospatial Engineering, GIS, or a related field Masters

Skill Qualifications
Skill Level

Certification in Data Analytics or Data Engineering Expert
Certification in Geospatial Technology Expert

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