Lead Data Engineer
UNiDAYS · London, United Kingdom ·
- Work mode
- Hybrid
- Seniority
- Lead
- Category
- Data engineering
UNiDAYS · London, United Kingdom ·
As a Lead Data Engineer, you will act as the technical authority within the data engineering team, responsible for defining how data solutions are designed and built across the organisation.
You will own the day-to-day technical direction of the data platform, ensuring that pipelines, data models, and warehouse structures are scalable, maintainable, and aligned to best practice.
Working closely with the Data Engineering Manager and the Head of Data Engineering & Governance, you will translate strategic direction into practical engineering approaches, while mentoring engineers and driving high technical standards across the team.
This is a senior individual contributor role with significant influence, operating as a peer to the Data Engineering Manager, with a focus on technical leadership rather than people management.
Technical Ownership & Architecture
Own the technical design and implementation approach for data pipelines, warehouse models, and transformations
Define and evolve data modelling standards (e.g. star schema, incremental models, partitioning strategies)
Ensure solutions are scalable, performant, and cost-efficient across the data platform
Review and approve technical designs and code across the team
Act as the primary escalation point for complex technical challenges
Data Platform & Warehouse Ownership
Act as the day-to-day technical owner of the data warehouse (BAU)
Ensure consistency and maintainability across datasets, pipelines, and transformations
Drive improvements in performance, reliability, and observability
Lead technical input into the data warehouse rebuild and future evolution
Engineering Standards & Best Practice
Define and enforce engineering standards, patterns, and reusable components
Promote strong practices in:
version control
testing and validation
CI/CD for data pipelines
Ensure high-quality documentation of data models and pipelines
Identify and address technical debt proactively
Data Quality & Reliability
Lead implementation of data quality checks and monitoring frameworks
Ensure pipelines are robust, observable, and alerting appropriately
Drive improvements beyond basic checks (e.g. volumetric, anomaly detection, trend validation)
Support root cause analysis and resolution of data incidents
Technical Leadership & Mentorship
Provide hands-on technical guidance to engineers and senior engineers
Mentor team members on system design, coding standards, and problem-solving
Lead technical discussions, design reviews, and knowledge sharing
Support capability uplift across the team
Collaboration & Translation
Work closely with:
Analytics & Reporting
Data Science / ML
Platform Engineering
Translate business and analytical requirements into scalable engineering solutions
Partner with stakeholders to ensure solutions are fit for purpose and usable
Delivery Contribution
Contribute to scoping and estimation of complex work
Partner with the Data Engineering Manager to ensure:
technical feasibility
appropriate sequencing of work
Focus on how work should be done, not managing delivery processes
COMPETENCIES
Data Architecture & Engineering
Detail: Designing scalable pipelines, modelling data flows, and building robust warehouse architectures.
At this level: Owns and defines how systems are built. Sets modelling standards, ensures consistency across pipelines, and makes pragmatic design decisions balancing speed, cost, and scalability.
Programming & Automation
Detail: SQL, dbt, Python, orchestration, CI/CD.
At this level: Expert practitioner. Produces high-quality, maintainable code and sets the standard for others. Introduces automation, testing, and deployment best practices across the team.
Data Quality & Observability
Detail: Monitoring, validation, reliability, incident handling.
At this level: Leads implementation of robust quality frameworks. Moves beyond basic checks to proactive monitoring and anomaly detection. Ensures trust in data outputs.
Technical Leadership
Detail: Mentoring, design authority, technical direction.
At this level: Acts as the go-to technical authority. Guides engineers in design decisions, challenges approaches, and elevates the overall technical capability of the team.
Problem Solving & Decision Making
Detail: Breaking down complex technical challenges.
At this level: Resolves ambiguous problems independently. Proposes clear, structured solutions and articulates trade-offs effectively..
Collaboration & Influence
Detail: Working across teams, translating needs into solutions.
Extensive experience in data engineering and data warehouse development
Strong track record of designing and implementing scalable data pipelines
Deep expertise in SQL and modern ELT tools (e.g. dbt or equivalent)
Experience working with cloud data platforms (AWS preferred: Redshift, S3, Athena, etc.)
Experience optimising data models for performance, scalability, and cost
Proven experience leading technical design and code quality across a team
Experience implementing CI/CD and version-controlled workflows
Familiarity with data quality, lineage, and monitoring practices
Experience working closely with analytics, reporting, or data science teams
Strong experience with Linux and or Unix command line including Bash/Shell scripting
Experience with data pipeline orchestration and scheduling
Knowledge of data governance, lineage, and quality monitoring practices.
Knowledge and experience of Airflow, Fivetran and Google Big Query
Academic Qualifications:
BSc Computer Science (or equivalent)
Technical Qualifications:
Strong SQL skills
Talend Data Integration (or similar ETL platform)
dbt Integration (or similar ETL platform)
Linux and or Unix command line familiarity including shell scripting
Certification in AWS data systems (or similar cloud platform) desirable
Tableau Desktop/Server (or similar reporting system)
This is your opportunity to Join the world’s largest student verification network and help shape the future of how brands connect with the next generation. We engage a community of 23M+ verified students and graduates across 115 markets, making us a truly global platform. Our brand is a powerhouse in the UK, and we’re rapidly accelerating our presence worldwide—especially in the US, Germany, India, France, Canada, and Australia.
We partner with 850+ of the world’s biggest brands, bringing their products and services to the hearts and minds of tomorrow’s professionals—driving engagement, building affinity, and delivering real results.
We offer a fast-paced, fun, and social working environment where you can truly make an impact. We believe work should enhance and complement your life, which is why we provide a hybrid working model. You will work together in person a minimum of 2 days per week and work from home for up to 3 days a week.
We work hard at UNiDAYS, and we believe in fair compensation for that hard work. That’s why we’re proud to offer all employees full access to our comprehensive benefits package.
Our perks include:
25 days holiday per year increasing with length of service, plus bank holidays
Competitive salaries
4pm finishes every Friday
Company pension scheme
Private health insurance (BUPA)
Dental Insurance (BUPA)
Income protection policy
Life assurance policy
Employee Assistance Program
Enhanced parental leave pay
Regular team building activities
£150 pounds towards your home office set up
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status or disability status.