Data Tech Lead

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

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

· 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.

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