Data Engineering Manager

AKT London
London
6 days ago
Create job alert
Data Engineering Manager. London. Hybrid Remote. ££Competitive.

AKT (pronounced “act”) is The Personal Performance Company with multi award-winning body care that may change your life. Founded by West End stars Ed Currie and Andy Coxon, AKT is by and for those who are “Born to Perform” — on the stage, at work, or in life.


In 2020, The Deodorant Balm made its stunning debut to rave reviews and awards from Vogue, GQ, Esquire, and Harper’s BAZAAR. Plastic‑free, aluminium‑free, and gender‑free, The Deodorant Balm instantly resonated with those looking for a natural deodorant that genuinely worked. Five fragrances and over 700,000 happy armpits later, The Deodorant Balm is already becoming a household name.


To this day, every new AKT product is put through its paces by London’s hard‑working theatre community to ensure it lives up to the high standards of its founders. As a rule, AKT’s products don’t break character — ever. It’s this effectiveness that has propelled AKT from the backstage to bathroom cabinets, bedside tables, duffel bags, and carry‑on luggage worldwide. And the good news is — the performance is just getting started.


About The Role:

As Data Engineering Manager you will lead the development and evolution of our data platform, tooling, and architecture to power a fast‑scaling, omnichannel D2C business. Operating across Shopify, Amazon, TikTok Shop, and retail channels, this role ensures we have a trusted, scalable, and efficient data ecosystem that supports growth, efficiency, and confident decision‑making across the business.


This person will balance hands‑on technical leadership with strategic platform management, overseeing the design and delivery of data pipelines, integrations, and models that unify data from multiple systems, geographies, and distribution centres.


Data, and this role, is critical to the success of AKT’s continued growth, and as such this role is high profile, impactful and will work very closely with the Head of Data and the Data & Insight team. You will work across multiple stakeholders, functions and external partners as needed.


The role will be based in the UK (and work UK hours) but will liaise occasionally with stakeholders from the USA and other territories so some flexibility is required.


Data Platform Strategy & Governance (25%)

  • Define future proof infrastructure strategy, architecture and tooling
  • Own roadmap, manage vendors and RFP processes
  • Oversee the design, build, and ongoing enhancement of an enterprise data platform on Snowflake
  • Provide mentorship, direction and training to the Data & Insight team regarding engineering practices
  • Ensure the platform is compliant and secure
  • Drive innovation and continuous improvement across data engineering
  • Ensure data quality, reliability and system performance across all infrastructure
  • Ensure all technical decisions are well‑justified, documented, and aligned with business needs

Data Pipelines & APIs (35%)

  • Develop, scale and monitor robust ETL/ELT pipelines for the ingestion of standard and non‑standard datasets
  • Integrate new data sources, via current and new ELT tools, and direct APIs where necessary
  • Support and productionise machine learning initiatives through scalable data foundations and robust architecture
  • Oversee monitoring of live data products and lead response to data incidents

Data Architecture & Modelling (25%)

  • Establish best practices for data modelling, designed to enable rapid dashboards, experimentation and reliable insights
  • Drive improvements in data quality and coverage, working with data owners and managers
  • Ensure data quality, reliability and system performance
  • Write advanced SQL, in DBT and Snowflake, to develop efficient and robust data models that provides the foundations of the AKT data platform

AI Readiness (15%)

  • Develop a semantic layers and data models specifically for optimal AI use in ThoughtSpot BI, and integration into other platforms

About You:

  • Demonstrable experience of high numeracy, strong attention to detail and the ability to solve problems.
  • Expert SQL skills, ideally using cloud databases.
  • Deep understanding and experience in data architecture, modelling and governance (e.g. Snowflake, BigQuery, etc.)
  • Proficiency in Python, SQL, DBT, Airflow, FiveTran, Rivey, and CI/CD, or similar, for data pipelines.
  • Demonstrated ability to prepare and manage data for AI/ML systems, including feature store design and data versioning
  • Strong grasp of data quality, observability, and lineage tooling (e.g. Monte Carlo, DataHub, Great Expectations)
  • Knowledge of building statistical and machine learning models such as attribution, classification, causal inference, forecasting using python, or similar.
  • Familiarity with reverse ETL and data activation tools (e.g. Hightouch, Census).
  • Experience in multi‑country data management including localisation, compliance, and performance optimisation.
  • Experience managing workload and projects, identifying data needs and scoping requirements that correspond to the business needs.
  • Experience working in a fast paced, ecommerce, B2C and/or subscription business.

Backstage Perks

  • Make a real impact on our next act by joining AKT at an exciting stage of growth, following our recent USA, Australia and New Zealand launches.
  • Flexible working: work from home, at our Oxford Circus office (which comes with gym access), or in co‑working spaces across the UK. We’ll reimburse you if you prefer a co‑working space over working from home.
  • Monthly team days in London to connect with the AKT ensemble.
  • Be part of a collective of creatives where the arts underpin everything we do.
  • A funny, kind, and inclusive work environment — we are banter, but we get sh*t done.
  • Allowance for products to give you the confidence to step onto the stage and perform.
  • Intervals encouraged: 36 days holiday, including bank holidays (pro‑rata for part‑time roles)
  • Pension contribution matching via salary sacrifice up to 5% of your salary.

Everybody is welcome

AKT London is for everyone. We believe that an inclusive work environment and a diverse, empowered team are key to achieving our mission. Our products are gender free and built for every BODY to help give them the confidence to step onto their stage – whatever that may be – and PERFORM. Our work environment is no different.


AKT London is an equal opportunity employer. We do not discriminate on the basis of race, colour, ancestry, religion, national origin, sexual orientation, age, citizenship, marital or family status, disability, gender identity or expression, veteran status, or any other legally protected status. We commit to a focused and sustained action to dismantle racist systems, policies, practices, and ideologies within ourselves and our networks. We have zero tolerance for intolerance. With our Founders belonging to a minority community, we commit to difference and diversity from the beginning, and we know what a rich and creative work environment can cultivate.


Anybody and everybody, to whoever is reading: we welcome you!


If you're a driven and hungry professional with a passion for beauty and sustainability, and you're ready to make a significant impact in a fast‑growing start‑up, we'd love to hear from you. Join us in redefining personal care while looking after our planet!


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager...

Data Engineering Manager

Data Engineering Manager

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.