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- Tasks: Lead the data engineering function and build robust data infrastructure for real-time decision-making.
- Company: Fast-scaling tech business with a focus on innovation and user experience.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Why this job: Shape the future of data engineering in a dynamic, engineering-driven environment.
- Qualifications: 7+ years in data engineering, expertise in Python, SQL, and cloud technologies.
- Other info: Join a team that values technical excellence and offers mentorship opportunities.
The predicted salary is between 110000 - 130000 ÂŁ per year.
This is an exciting opportunity to step into a high‑impact Lead Data Engineer role within a fast‑scaling, fully remote tech business. You’ll shape their data engineering function, lead technical direction, and build modern, robust data infrastructure that directly powers real‑time product and commercial decision‑making.
They are a next‑generation digital platform operating in a fast‑growing consumer market, backed by recent multi‑million Series C investment. Their product is built around best‑in‑class engineering, modern design, and a mission to deliver an intuitive, mobile‑first user experience. With strong year‑on‑year growth, they are now expanding their data function to support scale, performance, and product innovation.
You’ll be joining an engineering‑driven environment where data is central to the product and where technical excellence is genuinely valued.
As Lead Data Engineer, you will act as both a hands‑on technical expert and a mentor to a growing team. Responsibilities include:
- Leading the technical strategy for data engineering across ingestion, modelling, orchestration, and automation.
- Building and maintaining high‑quality ETL pipelines using modern tooling and cloud‑native infrastructure.
- Developing robust data models and frameworks to support analytics, reporting, and product teams.
- Championing best practices across testing, version control, monitoring, and CI/CD.
- Collaborating with engineering and data leadership to align technical decisions with broader business strategy.
- Mentoring mid‑level and senior engineers, raising the bar on technical capability and engineering quality.
Requirements:
- 7+ years’ experience in data engineering.
- Deep expertise in Python and SQL.
- Strong experience building ETL pipelines and distributed data systems.
- Solid cloud experience — ideally AWS (open to GCP).
- Experience with modern data warehouses such as Snowflake, Redshift, or BigQuery.
- Strong data modelling capability (dimensional modelling, Data Vault, etc.).
- Background in software engineering or backend development is highly desirable.
- Experience with dbt, Fivetran, AWS Glue, or Apache Iceberg.
Lead Engineer/Data Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Engineer/Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend virtual meetups, and engage with professionals on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving ETL pipelines and cloud infrastructure. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, SQL, and modern data warehouses. Practice common interview questions and think about how you can demonstrate your leadership abilities.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role.
We think you need these skills to ace Lead Engineer/Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Engineer role. Highlight your experience with Python, SQL, and building ETL pipelines. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our mission. Let us know why you're excited about this opportunity at StudySmarter.
Showcase Your Projects: If you've worked on any relevant projects, don’t hold back! Include links or descriptions of your work with modern data warehouses or cloud infrastructure. We love seeing practical examples of your expertise.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the attention you deserve. We can't wait to hear from you!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, SQL, and cloud platforms like AWS or GCP. Brush up on your experience with ETL pipelines and data modelling techniques, as these will likely come up during technical discussions.
✨Showcase Your Leadership Skills
As a Lead Data Engineer, you'll be expected to mentor others and lead technical strategies. Prepare examples of how you've successfully led teams or projects in the past, focusing on your ability to raise the bar on technical capability and engineering quality.
✨Align with Their Vision
Research the company’s mission and values, especially their focus on delivering an intuitive, mobile-first user experience. Be ready to discuss how your technical decisions can align with their broader business strategy and contribute to product innovation.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in real-time situations. Think about challenges you've faced in building data infrastructure or optimising ETL processes, and be ready to explain your thought process and the outcomes.
