Senior Software Engineer - Data Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Software Engineer – Data Engineer based in United Kingdom.

We are looking for an experienced Senior Data Engineer to design, build, and maintain scalable data infrastructure that powers analytics, reporting, and data-driven product development. In this fully remote role, you will take end-to-end ownership of ETL/ELT pipelines, transforming complex raw data into reliable, well-structured, and accessible datasets. You will work with modern cloud platforms, data warehousing technologies, and programming tools to deliver robust, high-performance data solutions. Collaborating with engineering, product, analytics, and data science teams, you will translate business requirements into dependable data architectures. You will also play a key role in improving data quality, system observability, scalability, and cost efficiency across production environments. This opportunity offers the chance to tackle challenging engineering problems alongside an international team of talented professionals, with flexible working arrangements and opportunities for continuous growth.

Accountabilities:

• Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from diverse internal and external sources.

• Data Modeling and Architecture: Develop and optimize data models, schemas, and transformation logic to support analytics, reporting, business intelligence, and downstream application requirements.

• Data Quality and Reliability: Establish and maintain data validation processes, quality checks, and reliability standards to ensure datasets remain accurate, consistent, and trustworthy.

• Pipeline Monitoring and Troubleshooting: Monitor pipeline performance and health, independently investigate data issues, identify root causes, and implement effective solutions to minimize disruptions.

• Observability and Alerting: Implement monitoring, alerting, and observability practices that improve visibility into production data systems and enable proactive incident detection and resolution.

• Cloud Data Infrastructure: Build and maintain data solutions using cloud platforms and modern data warehousing technologies, ensuring systems remain scalable, secure, and efficient.

• Performance and Cost Optimization: Identify opportunities to improve processing speed, resource utilization, scalability, and the cost-effectiveness of existing data infrastructure.

• Cross-Functional Collaboration: Partner with analytics, product, data science, and engineering teams to understand their data requirements and translate them into durable, well-designed technical solutions.

• Testing and Engineering Standards: Contribute to team standards for code quality, automated testing, code reviews, deployment practices, and maintainable data engineering workflows.

• Technical Documentation: Create clear and comprehensive documentation covering data pipelines, models, schemas, infrastructure, and operational procedures to support knowledge sharing and maintainability.

• Production Support: Participate in on-call rotations and incident response activities as needed, helping ensure the stability, availability, and reliability of production data systems.

• Continuous Improvement: Evaluate new technologies, tools, and engineering practices that can strengthen the data platform and improve the effectiveness of the wider engineering organization.

Requirements:

• Professional Experience: At least four years of professional experience in data engineering or a closely related technical discipline, with a strong track record of delivering production-ready data solutions.

• SQL Expertise: Strong SQL skills, including the ability to query, transform, analyze, and optimize complex datasets efficiently.

• Programming Skills: Proficiency in at least one programming language commonly used in data engineering, such as Python, Scala, or Java.

• ETL/ELT Pipeline Experience: Hands-on experience designing, implementing, operating, and maintaining ETL/ELT pipelines in production environments.

• Cloud Platform Knowledge: Practical experience with at least one major cloud data platform, such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

• Modern Data Warehousing: Experience working with contemporary data warehousing technologies and designing solutions that support reliable data access and downstream analytics.

• Data Modeling and Quality: Solid understanding of data modeling principles, schema design, data quality management, and pipeline orchestration.

• Troubleshooting and Problem-Solving: Ability to work independently with large, complex datasets, diagnose data issues, and implement effective solutions in production systems.

• Scalability and Reliability: Understanding of the engineering principles required to build robust, maintainable, and cost-efficient…