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About Sedex
Sedex is a trusted partner for over 100,000 businesses worldwide, helping them create socially and environmentally sustainable supply chains. Through our platform's powerful data insights and expert guidance, we simplify the management, assessment, and reporting of sustainability performance.
Our Vision is to be a leader in making global supply chains more socially and environmentally sustainable. Our Mission is To provide data-driven insights, accessible tools, and exceptional services that support businesses in improving environmental, social, and governance (ESG) performance and outcomes.
The Role
We are looking for an experienced, hands-on Tech Lead to lead engineering within the data platform and data products of our SaaS business.
You will lead a small cross-functional data pod building and evolving the pipelines, models and services that turn supply chain data into customer-facing insight. The role combines hands-on data engineering, technical leadership and architectural ownership.
You will also line-manage your pod's engineers, taking responsibility for their performance, growth and wellbeing.
We expect our Tech Leads to be exceptional engineers first — people who lead through the quality of their thinking and the systems they build.
Key Responsibilities
In the First Four Weeks
- Get to know your pod's engineers, their goals and development needs, and establish your 1:1s
- Familiarise with the data domains, pipelines and systems your team owns, and how data flows through them
- Understand the production environment and deployment approach, and begin monitoring pipeline health and data quality metrics
- Begin driving solutions within your domain, and contributing to those of others via architectural reviews
- Build relationships cross-team and cross-function, including with data suppliers, analysts and consumers
Ongoing Responsibilities
Build and Lead the Technical Direction
You will design and build the pipelines, data models and services your pod owns, and guide their technical direction:
- Designing maintainable ingestion, ETL/ELT and data serving architectures
- Implementing high-quality, test-driven production code in Python and SQL
- Designing relational, non-relational and warehouse data models, including in Snowflake
- Ensuring pipelines and services are scalable, observable, reliable and cost-effective
- Making pragmatic trade-offs between speed and sustainability, and evolving systems as product requirements grow
- Leading through technical credibility and example
Own Data Quality
You are accountable for the trustworthiness of the data your pod produces:
- Co-creating and maintaining data contracts with suppliers, producers and consumers, internal and third party
- Establishing automated data quality testing alongside code testing
- Building lineage, cataloguing and documentation to the point where others can self-serve
- Meeting governance, privacy and security obligations in how data is handled
- Making data quality and freshness visible, and holding the team to account
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Line Management
You will line-manage the engineers in your pod. This is core to the role, not an afterthought:
- Running regular 1:1s and providing ongoing feedback
- Supporting each engineer's professional development and career growth
- Setting clear expectations and holding people to account
- Creating a psychologically safe environment where people feel free to highlight risk, challenge ideas, and acknowledge mistakes
- Contributing to hiring decisions for your team
Improve Engineering Productivity
A central part of the role is improving how the team builds software:
- Remove technical bottlenecks and friction
- Simplify architecture and data models where possible
- Improve development workflows, local data environments and CI/CD processes
- Introduce automation where it improves delivery speed or reliability
AI-Assisted Development
AI tools are reshaping how software and data systems are built. We expect our Tech Leads to lead that shift, raising the capability of the whole team and not just their own:
- Use AI coding assistants daily — writing and refactoring pipeline code, drafting and optimising SQL, generating tests and data quality checks, and exploring unfamiliar datasets and schemas
- Coach your pod on effective AI-assisted workflows, including how to critically review generated code, SQL and data models, and when not to use these tools
- Evaluate emerging tooling, including data-specific tools such as assisted SQL authoring, schema generation and semantic layers, and make pragmatic adoption decisions
- Set standards for how AI-generated code and transformations are reviewed and tested, holding a higher bar where output shapes customer-facing data — a corrupted dataset costs more than code that fails loudly
- Track the productivity gains from AI-assisted development and use that data to refine practice
Communication
- Collaborate with Product, Data Analytics and UX early in solutioning, ensuring technical considerations are represented in decisions
- Communicate clearly, internally and externally, how the team contributes to organisational goals and priorities
- Proactively take steps to highlight risk
Delivery
- Champion agile best practices and continuous delivery, working with Product to break deliverables into thin vertical slices that deliver value early
- Challenge the team to justify approaches based on cost-benefit and business value
- Proactively identify and work through cross-team dependencies that may delay delivery
- Foster a security-first approach
Knowledge, Skills & Experience
We're looking for engineers who combine technical depth, productivity, and pragmatic decision-making. You should have:
- 3–5 years' experience working in data teams at a senior level
- Strong production experience building data pipelines and services in Python and SQL
- The ability to design relational, non-relational and Snowflake warehouse data models, and a good grasp of modern patterns for ingestion, ETL/ELT, quality, governance and DataOps
- Experience co-creating data contracts with data suppliers and consumers, and integrating with their systems
- Experience driving automated testing in both code and data, using TDD and data quality testing
- Experience defining and optimising non-functional requirements such as performance, maintainability and cost
- Experience operating data systems in production cloud environments
- A year or more working with AI coding assistants, able to articulate their benefits and limitations
- Experience mentoring, coaching, or line-managing other engineers
- Excellent communication skills
- Strong experience working with Agile methodologies


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Bonus points for:
- Real-time, message-based architectures using technologies like Apache Kafka
- Expertise in ML and AI data pipelines
- A software engineering background, able to contribute to backend services and their cloud-native tooling (Docker, Kubernetes, Terraform)
Our Culture
At Sedex, our approach to business and culture is firmly rooted in our core values, which guide everything we do:
- Respect Each Other: We believe that a foundation of mutual respect is essential to creating a positive and inclusive environment.
- Customer-Driven: We are passionate about delivering exceptional value to our customers. By listening to their needs, understanding their challenges, and continuously adapting our solutions, we aim to empower them to achieve their sustainability goals and drive positive change in their supply chains.
- Thinking Creatively: Innovation is at the heart of our work. We encourage creative problem-solving and embrace new ideas that challenge the status quo. This mindset allows us to continuously improve our products and services, offering fresh and effective solutions to complex sustainability and ethical sourcing issues.
- Take Ownership: We empower our team members to take responsibility for their actions and outcomes. Every person at Sedex is encouraged to own their work, make decisions with confidence, and contribute proactively to the success of the team and the business.
- Deliver Results: We are results-oriented and committed to delivering tangible, impactful outcomes for our customers, our business, and society at large.
Privacy Policy
Sedex is committed to protecting the privacy of its website users and members. Sedex uses any personal information you submit to us in accordance with this policy. The General Data Protection Regulation (GDPR) requires us to ensure that any personal information you provide us is processed fairly and lawfully. Sedex is the data controller in relation to any personal information you submit. Click here to view our privacy policy.
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