SLR Consulting
Data Engineering Lead

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Job Summary
We're looking for a Data Engineering Lead to provide technical and operational leadership for our data engineering capability, ensuring the platforms, pipelines, and data assets that underpin enterprise reporting and analytics are scalable, trusted, and aligned with long-term business needs.
This role combines hands-on technical leadership with strategic ownership of the data engineering function. You will lead the design and evolution of the data engineering ecosystem, enforce engineering standards and best practices, and guide the delivery of high-quality data solutions across the organisation.
You’ll work closely with analytics, BI, platform, and business stakeholders to ensure that data is managed as a strategic asset, and that the data platform continues to evolve in support of growing reporting, analytics, digital, and AI-driven use cases.
Key Responsibilities
Data Engineering Leadership
- Own the design and evolution of the enterprise data platform, ensuring it supports current reporting requirements and future analytics, AI, and digital capabilities.
- Partner with enterprise and solution architects to align data engineering solutions with wider technology strategy and architecture standards.
- Drive adoption of modern data architecture approaches, including lakehouse and warehouse patterns, data product thinking, and reusable engineering services.
- Mentor and support data engineers through technical coaching, knowledge sharing, and career development activities.
- Evaluate and recommend new technologies, tooling, and approaches that improve efficiency, reliability, and scalability.
Delivery & Engineering Excellence
- Oversee the design, development, and operation of data pipelines, transformation frameworks, and curated analytical datasets.
- Ensure robust implementation of data quality, monitoring, observability, operational controls, and governance requirements.
- Lead the delivery of scalable data integration solutions across APIs, event-driven architectures, batch processing, and file-based integration patterns.
- Establish and govern engineering practices including CI/CD, automated testing, version control, infrastructure-as-code, and technical documentation.
- Drive platform performance, reliability, maintainability, and cost optimisation initiatives.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Stakeholder Engagement & Data Strategy
- Work closely with analytics, BI, and business stakeholders to understand priorities and translate them into scalable engineering solutions.
- Help shape the enterprise data roadmap and prioritise investments that maximise business value.
- Participate in strategic planning and provide input into data governance, operating models, and capability development.
- Champion data-driven decision-making and promote the adoption of trusted, well-governed data assets across the organisation.
What We're Looking For
Essential Experience / Skills
- Significant experience leading the design, development, and operation of enterprise-scale data engineering platforms and teams.
- Strong technical expertise in SQL and Python, PySpark, or equivalent technologies for data ingestion, transformation, and validation.
- Experience with Microsoft Fabric or similar modern cloud-based analytics and data platforms.
- Strong experience designing and governing analytical data models using recognised patterns such as Medallion Architecture, star schema, and snowflake schema.
- Experience leading technical teams, mentoring engineers, and establishing engineering standards and delivery practices.
- Experience developing and implementing data quality, monitoring, governance, security, and operational controls at scale.
- Strong understanding of software engineering principles, including CI/CD, testing, version control, and automation.
- Ability to communicate effectively with senior technical and non-technical stakeholders and influence decision-making.
- Experience balancing strategic planning with hands-on technical leadership and delivery.
Desirable Experience / Skills
- Experience with enterprise business systems such as ERP, HR, and CRM platforms.
- Experience defining data platform roadmaps and leading platform transformation initiatives.
- Experience supporting enterprise reporting and analytics environments with strong governance and regulatory requirements.
- Familiarity with business-critical domains such as finance, operations, commercial, or people data.
- Experience supporting data platforms intended to enable advanced analytics, machine learning, or AI use cases.
- Experience operating within a product-based or data-product delivery model.


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Why Join / Opportunity
- Lead the evolution of a strategically important enterprise data platform.
- Shape the future direction of data engineering within a growing analytics & AI capability.
- Influence architecture, technology choices, engineering standards, and delivery practices across the organisation.
- Develop a high-performing data engineering function with clear ownership and impact.
- Work with senior stakeholders to drive meaningful business outcomes through trusted and scalable data solutions.
- Help establish the foundations required to support future analytics, AI, and wider digital transformation initiatives.
- Create a lasting engineering capability that enables the organisation to make better decisions through data.
About Us
SLR are global leaders in Sustainability Solutions, helping our clients achieve their sustainability goals. We are a consultancy with 4000+ employees across 6 regions in over 125 countries. Our ‘one team’ culture is at the heart of our business, providing a collaborative and supportive environment for professional development.
Along with competitive salaries, our staff enjoy a comprehensive benefits package with a company pension plus excellent healthcare offering, travel and life insurance and a structured career framework with regular reviews offering outstanding opportunities for progression. Alongside 25 day’s annual leave, with additional flexible bank holidays, we offer flexible, agile and hybrid working which enables staff to tailor hours worked around core hours, with family friendly policies help balance the needs of professional and home life.
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