Data Engineer

We are looking for a Data Engineer who will be a key member of the Service Delivery team, responsible for designing, building, and maintaining scalable data pipelines and data products that support analytics and operational decision-making across the organisation.

This role is critical in ensuring data is reliable, accessible, and aligned to business needs, working across a variety of data sources and platforms to deliver high-quality, production-ready solutions.

The successful candidate will have strong technical expertise combined with excellent communication and problem-solving skills. They must be comfortable working across teams, translating requirements into robust technical solutions, and managing data pipelines end-to-end.

Pragmatic, data-driven, detail-oriented, and self-motivated are essential traits for success in this role, along with a mindset focused on scalability, reliability, and continuous improvement.

What You'll Do

- Design, build, and operate end-to-end ETL/ELT pipelines across ingestion, transformation, and serving layers.

- Architect scalable, reusable data pipelines and frameworks that balance performance, cost, and reliability.

- Implement incremental loads, schema evolution, and data contracts to ensure stable, production-grade pipelines.

- Monitor and maintain pipelines, including logging, validation, alerting, and incident response.

- Collaborate closely with BI, analysts, and architects to ensure datasets meet business requirements, SLAs, and reporting needs.

- Lead complex incident investigations and root-cause analysis, driving remediation and prevention.

- Review and improve code, pipelines, and models to ensure quality, maintainability, and reuse.

- Translate requirements into technical designs with clear constraints, SLAs, and acceptance criteria.

- Mentor junior engineers and contribute to standards, patterns, and best practices across the team.

What You'll Bring

- Strong ownership mindset: ability to move from task execution > pipeline ownership > system design accountability.

- Ability to balance scale, latency, cost, and governance when making design decisions.

- Solid communication skills to:

- Explain technical trade-offs clearly to technical and non-technical stakeholders

- Provide proactive updates on risks, changes, and dependencies

- Align teams across engineering, BI, and business domains

- Structured and proactive working style:

- Deliver maintainable solutions with strong documentation and observability

- Identify issues early and escalate appropriately

- Drive continuous improvement in reliability and engineering practices

- Strong problem-solving capability:

- Diagnose complex failures and data issues systematically

- Build reusable patterns to reduce duplication and operational load

- Mentoring mindset:

- Guide junior engineers

- Improve team quality through reviews, standards, and shared practices

Technical Skills

- Data Modelling: Designs analytical data models for multiple consumers, understands schemas, keys, and data grain, and balances normalisation versus performance using established and reusable modelling patterns.

- Data Governance: Embeds governance into pipeline and data model design, including lineage, traceability, ownership, and data quality rules, while ensuring alignment with data classification and compliance requirements.

- ETL / Data Engineering: Designs, builds, and operates end-to-end ETL/ELT pipelines, including incremental processing, idempotent patterns, and schema evolution, with a focus on scalability and reliability.

- Development (SQL / Python): Writes clean, optimised SQL and scalable Python code, applying modular design, logging, testing, and code review practices, while considering performance and scalability trade-offs.

- Data Products / BI Integration: Designs and delivers datasets and data products with clearly defined SLAs, ensuring compatibility with BI tools and alignment with reporting and analytics requirements.

- Data Quality & Testing: Implements automated validation, schema checks, and monitoring, and leads investigations into data quality issues to identify root causes and prevent recurrence.

- Architecture & Scalability: Makes informed design decisions across batch vs streaming and ETL vs ELT approaches, building reusable, scalable components that improve platform efficiency and reliability.

- Security & Governance: Applies security-by-design principles, including access controls, data masking, and compliance enforcement, and supports audits through strong traceability and documentation.

It is impossible to list every requirement for, or responsibility of, any position. Similarly, we cannot identify all the skills a position may require since job responsibilities and the Company's needs may change over time. Therefore, the above job description is not comprehensive or exhaustive. The Company reserves the right to adjust, add to or eliminate any aspect of the above description. The Company also retains the right to require all employees to undertake additional or different job responsibilities when necessary to meet business needs.

Solera is a global leader in data and software services that strives to transform every touchpoint of the vehicle lifecycle into a connected digital experience. In addition, we provide products and services to protect life's other most important assets: our homes and digital identities. Today, Solera processes over 300 million digital transactions annually for approximately 235,000 partners and customers in more than 90 countries. Our 6,500 team members foster an uncommon, innovative culture and are dedicated to successfully bringing the future to bear today through cognitive answers, insights, algorithms and automation. For more information, please visit solera.com.