Data Engineer at ENGIE Energy Access

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Job Title: Data Engineer

Location: Lagos

Job type: Full-time

Reporting line: Head of Data

About ENGIE Energy Access:

ENGIE Energy Access is one of the leading Pay-As-You-Go (PAYGo) and mini-grids solutions provider in Africa, with a mission to deliver affordable, reliable and sustainable energy solutions and life-changing services with exceptional customer experience. The company is a result of the integration of Fenix International, ENGIEMobisol and ENGIEPowerCorner; and develops innovative, off-grid solar solutions for homes, public services and businesses, enabling customers and distribution partners access to clean, affordable energy.

ThePAYGosolar home systems are financed through affordable installments from $0.19per day and the mini-grids foster economic development by enabling electrical productive use and triggering business opportunities for entrepreneurs in rural communities. With over 1,700 employees, operations in 9 countries across Africa (Benin, Coted’Ivoire, Kenya, Mozambique, Nigeria, Rwanda, Tanzania, Uganda and Zambia), over 1.2 million customers and more than 6 million lives impacted so far, ENGIE Energy Access aims to remain the leading clean energy company, serving millions of customers across Africa by 2025.

Job Purpose/Mission

This position will be part of the Global Data team. This is an incredible opportunity to join a high-performing team that is passionate about pioneering expanded financial services to off-grid customers at the base of the pyramid.
Key responsibilities will include building and maintaining data pipelines between our main transactional and analytics databases, IoT data delivered from devices, PBX, and our in-house ticketing system.
You would also be responsible for building pipelines to deliver data in realtime to our field team mobile application to allow data-informed decisions to be made in the field, as well as working with members of the data team to ensure high code quality and database design.
Your work will make a meaningful impact by enabling Engie to continuously innovate on how we support our customers in their repayment journey.

Responsibilities
Data Modelling and Extract, Transform and Load (ETL):

Design and implement robust data models to support analytics and reporting requirements.
Develop and maintain scalable ETL processes from various sources, including multiple ERP systems, into a data warehouse.

Data Ingestion and Automation data pipelines:

Implement data validation and quality checks to ensure accuracy and completeness.
Design, build, and maintain automated data pipelines to streamline data processing and transformation.
Utilize orchestration tools to schedule and monitor pipeline workflows.
Collaborate with data analysts to understand data requirements and support their analysis needs.
Optimize data structures and queries to enhance performance and usability for analytical purposes.

Data Warehousing:

Design and optimize data warehousing solutions to support business intelligence and analytics needs.
Implement data modelling techniques to organize and structure data for optimal querying and analysis.

Optimization and Performance Tuning of Data Dashboards:

Troubleshooting and fixing issues on existing reports/dashboards while also continuously building improvements.
Optimize dashboard performance and ensure responsiveness for large datasets and complex queries.
Design, Data Visualization and Dashboards

Qualifications and Experience

Bachelor’s or Master’s Degree in Computer Science, Machine Learning, or related field
5+ years of industry experience working on data engineering with a focus on data ingestion, data warehousing, pipeline automation, and ETL development
Experience building infrastructure to support streaming or offline data.
Extensive programming experience in Python/Scala/Java
Experience with SQL in addition to one or more of Spark/Hadoop/Hive/HDFS
Working knowledge of databases, data systems, and analytics solutions, including proficiency in SQL, NoSQL, Java, Spark and Amazon Redshift for reporting and dashboard building.
Experience with implementing unit and integration testing.
Ability to gather requirements and communicate with stakeholders across data, software, and platform teams.
Ability to develop a strategic vision for data pipelining and infrastructure.
Experience managing a team of mid-level engineers.
Sense of adventure and willingness to dive in, think big, and execute with a team