Senior Data Engineer
Description
Do you want to work to make Power for Good?
We're the world's largest independent renewable energy company. We're guided by a simple yet powerful vision: to create a future where everyone has access to affordable, zero carbon energy.
We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them.
RES is a family with a diverse workforce, and we are dedicated to the personal professional growth of our people, no matter what stage of their career they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally.
Our competitive package offers a wide range of benefits and rewards.
Job Summary
The Senior Data Engineer role is a unique opportunity to help build a world-class global data platform. You’ll be responsible for delivering products for our internal customers, designing, implementing, and maintaining complex data pipelines and infrastructure that will give RES a competitive edge. The Senior Data Engineer will be required to build relationships and collaborate with key stakeholders.
Accountabilities
Key accountabilities include but are not limited to:
- Architect build, implement and operate reliable, secure and observable data pipelines and curated datasets that power enterprise reporting, analytics and AI/ML use cases.
- Take ownership of engineering quality, automation and performance across the data platform, partnering with architecture, governance, modelling and reporting teams to deliver end-to-end data products.
- Lead and directly line manage the data engineering team driving a high performing team, accountability, innovation and the latest technology for automation, cost efficiency and innovation.
- Implement robust engineering standards and lead delivery of and oversee curated datasets with strong data quality controls and monitoring. Drive observability and optimise performance and cost
- Lead work across IT leadership, business domains and source system owners and integration teams to onboard new sources and validate extracts.
- Lead incident response strategy and implementation and continuous improvement for BAU operations; drive root cause remediation.
- Drive technical decisions, evaluate new technologies and tools, and contribute to the continuous improvement of our data ecosystem.
- Build our Data Platform and solve complex data problems to deliver insights helping to build our trading data platform.
- Foster a culture of sharing, mentor junior engineers, provide guidance, and drive excellence.
- Convert data engineering and architecture best practices in the Data and Engineering teams, building a data culture based on the highest quality and reliability standards.
- Lead AI/ML use cases by producing feature-ready datasets and supporting data scientists with efficient data access patterns.
Skills
The successful candidate will need to demonstrate:
- Leadership (this is a senior role where your leadership and mentorship skills are important to the success of the wider team).
- Advanced skills in Microsoft stack including Azure, Fabric, synapse, purview and PowerBI.
- Expert in data engineering tools and technologies including SQL, python and others.
- Strong problem-solving skills, operational mindset and ability to mentor, lead, train and QA engineers work.
- Innovation in the latest technologies for best practice engineering, including data and AI/ML.
- Strong, clear communication and stakeholder management and reporting of risk, change and impact.
- Enthusiastic about helping juniors develop and grow.
- The ability to thrive in this role which demands technical and data-driven results.
- Skilled in data engineering for AI/ML initiatives.
Qualifications and Experience
- Degree in a relevant field directly related to data.
- Significant experience delivering enterprise-grade data engineering solutions in production environments and leading teams to deliver high performance outcomes.
- Proven experience as a Senior Data Engineer, with a strong portfolio of building real-time data systems and teams using modern approaches.
- Extensive experience of working with Data and Analytics teams that provide in-depth analytics reporting capabilities across the business.
- Previous experience leading a small engineering team is essential, as is hands on current technical engineering experience.
- Extensive experience with Python including open-source data libraries and frameworks and messaging systems, along with proficiency in building out modern data warehouses.
- Azure mastery: Deep expertise in the Azure Ecosystem, specifically Azure Data Factory (ADF), Synapse, Unity Catalogue, Fabric, Purview: data lakes/lakehouse, data quality and testing frameworks and automation.
- Leading and maintaining security and privacy by design: access controls, handling of PII, auditability.
- Working knowledge of AI and machine learning data requirements.
- Demonstrated ability to lead and improve reliability, cost, performance and maintainability of data platforms.
- Building quality global datasets for BI and analytics consumption from many ingestion sources and leading/coaching and setting guardrails for regional data/analytics engineers and advising on projects.
- It is mandatory that you have proven experience in IFS (RES’s enterprise ERP system) and extensive experience in financial and human resources data and engineering in a global context.
- Working with third-party data providers and ingesting real-time data feeds.
At RES we celebrate difference as we know it makes our company a great place to work. Encouraging applicants with different backgrounds, ideas and points of view, we create teams who work together to solve complex problems and design practical solutions for our clients. Our multiple perspectives come from many sources including the diverse ethnicity, culture, gender, nationality, age, sex, sexual orientation, gender identity and expression, disability, marital status, parental status, education, social background and life experience of our people.