Job Description
Description
Company Overview
Welcome to HomeServe Finance, the newest innovation under the globally recognized HomeServe banner. As a fresh venture, we aim to solve the problem of CO2 emissions created by home heating and cooling. Using our parent company’s robust infrastructure and extensive reach, we will redefine the point-of-sale lending industry, making new renewable technology accessible and affordable to every homeowner. HomeServe, known worldwide for its commitment to exceptional service and customer satisfaction, brings decades of experience and a trusted reputation to our startup.
HomeServe Finance is dedicated to developing secure, accessible, and tailored financial solutions that meet the planet’s need to transition away from fossil fuel home heating and accelerate the transition to efficient, renewable energy-powered homes.
Joining us means not just a job but a chance to shape the future of finance and contribute to the global carbon reduction targets. We value creativity, integrity, and a collaborative spirit. If you want to significantly impact a dynamic environment where everything remains to be built, HomeServe Finance is your platform to excel and grow. We are committed to creating financial services that combine the best of technology and human touch while upholding the high standards of responsibility that the lending industry demands.
As a Data Engineer at HomeServe Finance, a pioneering startup of HomeServe, you will lead and manage the data pipelines that deliver timely, accurate data to management and engineering teams. Providing actionable data, and analytics tools to business analysts and engineering teams to enable accurate, actionable information. This position offers a unique opportunity to be part of a new venture within a well-established international group, where you can bring cutting-edge financial solutions to the market and contribute to our rapid growth.
Our cloud-native stack includes AWS, Terraform, Docker, DBT, and Python technologies.
Required Qualifications:
- Experience in Data Engineering using tools such as DBT, Spark, Python, AWS Athena, Presto, AWS Quicksight
- Bachelor’s degree in Computer Science, Statistics, Engineering, Science, or a related field.
- Experience with languages such as SQL, Python, and similar
- Great numerical and analytical skills
Requirements
Key Responsibilities
- Implement data flows to connect operational systems, data for analytics, and business intelligence (BI) systems
- Re-engineer manual data flows to enable automation, scaling, and repeatable use
- Write ETL (extract, transform, load) scripts and code to ensure the ETL process performs optimally
- Work with business teams to map business requirements to available data and propose opportunities based on existing and potential data pipelines
- Develop business intelligence reports that can be reused
- Build accessible data for analysis
- Build tooling to enable AI and ML pipelines with data