Analytics Engineer

Analytics Engineer

Full-Time 45000 - 55000 £ / year (est.) On-site
P

At a Glance

  • Tasks: Own and automate external reports, transforming manual work into efficient pipelines.
  • Company: Join Taptap Send, a fast-growing money movement business making a global impact.
  • Benefits: Competitive salary, growth opportunities, and the chance to learn from experienced engineers.
  • Other info: Dynamic startup environment with opportunities to tackle big challenges.
  • Why this job: Make a real difference by helping families with affordable remittances while developing your skills.
  • Qualifications: 1-2+ years in data roles, strong SQL skills, and a proactive attitude.

The predicted salary is between 45000 - 55000 £ per year.

Tired of being told "that's not your scope"?

Plenty of good analysts hit the same wall: you query the data but never build the pipelines, you're boxed into one lane, and more scope means waiting your turn.

Here, it's the opposite.

Taptap Send moves billions of dollars a month across 6 of 7 continents.

We're probably the largest, fastest-growing money movement business you've never heard of.

Cards, wallets, business-to-business payments, institutional payments, and new markets are all launching now, and each needs its data, reconciliations and reporting built from scratch.

That's your work.

The job You’ll own the external reports the business can't operate without, then automate them into reliable, reusable dbt models.

From day one you'll work with Finance, Compliance, Treasury, Product and Data Engineering to make sure every number is modelled correctly.

Own external reporting: deliver the datasets behind month-end close and regulatory reporting, on time, every cycle.

Automate: turn multi-day manual work into scheduled pipelines, runbooks and dbt models, so it only gets done once.

Get ahead of launches: build reports and reconciliations as each product and market goes live, before anyone asks.

Be first line for data requests: build models so people and AI agents can answer repeat questions themselves.

Keep data trustworthy: build tests, checks and alerts that catch reconciliation breaks and stale data before they become incidents.

Share what you know: peer-review code and join our weekly meetups.

Why you’ll want it Grow as fast as you're able.

We hire for potential, not years of experience.

On a lean, talent-dense team, you'll own real work early and take on more the moment you're ready.

Go from querying data to designing systems.

Data, product or business analyst?

You don't need to be an analytics engineer yet.

Build the pipelines behind the numbers, and learn dbt, testing, automation and AI tooling from senior analytics engineers.

Don't get boxed in.

Own the reporting, automate it, then take on our biggest problems wherever they sit.

Your hiring manager started in Finance and has since worked across Partner Ops, Fraud, Compliance, Reconciliation and Product.

See the whole business.

You'll follow a transfer from the moment a customer taps send, through partner payout and reconciliation, to the report a regulator reads.

Own numbers that matter.

Auditors and Finance rely on what you build.

This isn't a dashboard role.

Put more money in families' hands.

Remittances are a lifeline for millions of families and are worth more than all foreign aid.

Every report you automate helps us keep transfers cheap and reliable.

You’ll fit if you have 1-2+ years in a data or analytics role A technical or quantitative degree, or equivalent experience Strong SQL and experience wrangling messy, complex data Some experience automating repetitive work (e. g. scripts, scheduled jobs) A strong sense of ownership: when something is broken, ownerless or late, you step in, fix it, and make sure it doesn't happen again Reliability under deadlines, a "no task too small" attitude, and comfort chasing stakeholders The right to work in the UK Nice to have: startup or scale-up experience, Python or R, dbt, Looker or Mode, and something you've built, at work or on the side, because the manual way announced you. #J-18808-Ljbffr

Analytics Engineer employer: ProfilHQ

Canonical is an exceptional employer that champions a distributed work culture, allowing you to thrive in a flexible environment while collaborating with talented professionals from around the globe. With a strong focus on employee growth, we offer a generous personal learning and development budget, annual compensation reviews, and unique opportunities for international travel to connect with colleagues. Join us in London or remotely in EMEA time zones, and be part of a pioneering tech firm that values innovation, diversity, and excellence.

P

Contact Details:

ProfilHQ Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineer

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like ProfilHQ!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Analytics Engineer at ProfilHQ.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like ProfilHQ.

✨Apply Directly through Our Website

When you find a suitable opening like Analytics Engineer at ProfilHQ, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Analytics Engineer

SQL
Data Wrangling
Automation
dbt
Reporting
Data Modelling
Reconciliation

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at ProfilHQ, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ProfilHQ. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at ProfilHQ

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ProfilHQ!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.