Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

Anaplan
Manchester
1 week ago
Create job alert

At Anaplan, we are a team of innovators focused on optimizing business decision‑making through our leading AI‑infused scenario planning and analysis platform so our customers can outpace their competition and the market.


What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.


Our customers rank among the who’s who in the Fortune 50. Coca‑Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best‑in‑class platform.


Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.


Supported by operating principles of being strategy‑led, values‑based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next – together!


Team Description

The Data Engineering team is responsible for developing and maintaining the company’s data ingestion and processing pipelines. This role collaborates with data scientists, software engineers, business analysts, and technical leads to build reliable data infrastructure that supports decision‑making for apparel brands and retailers. The position reports to the Technical Lead within the Data Engineering function.


Your Impact

  • Contribute to the development and enhancement of data ingestion and processing pipelines
  • Partner with product managers, data scientists, and engineers to build and maintain accurate and robust data infrastructure managing first‑ and second‑party data
  • Collaborate with technical leads and senior engineers on data architecture decisions and implementation strategies
  • Support the team in delivering scalable solutions while learning and growing your expertise
  • Work as part of a collaborative team that values creativity and continuous improvement
  • Help build and maintain data pipelines that support AI and decision‑making tools

Your Qualifications

  • Commercial & proven experience in data engineering or related technical roles
  • Proficiency in SQL and Python for data processing and pipeline development
  • Experience with data warehousing concepts and ETL/ELT processes
  • Hands‑on experience with modern data platforms such as Snowflake, Databricks, or Redshift
  • Familiarity with data orchestration tools like Apache Airflow, Prefect, or DBT
  • Experience working with columnar formats like Parquet and Avro
  • Understanding of data modeling, database optimization, and performance tuning
  • Experience integrating data from various sources including APIs, FTP, and cloud storage

Preferred Skills

  • Knowledge of streaming data processing and data APIs
  • Knowledge of cloud platforms, particularly AWS
  • Familiarity with infrastructure as code and CI/CD practices
  • Experience with time series data

Our Commitment to Diversity, Equity, Inclusion and Belonging (DEIB)

We believe attracting and retaining the best talent and fostering an inclusive culture strengthens our business. DEIB improves our workforce, enhances trust with our partners and customers, and drives business success. Build your career in a place where diversity, equity, inclusion and belonging aren’t just words on paper – this is what drives our innovation, it’s how we connect, and it contributes to what makes us a market leader. We believe in a hiring and working environment where all people are respected and valued, regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes people unique. We hire you for who you are, and we want you to bring your authentic self to work every day!


We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive equitable benefits and all privileges of employment. Please contact us to request accommodation.


Fraud Recruitment Disclaimer

It has come to our attention that fraudulent and fictitious job opportunities are being circulated on the Internet. Prospective candidates are being contacted by certain individuals, mainly through telephone calls, emails and correspondence, claiming they are representatives of Anaplan. The main purpose of these correspondences and announcements is to obtain privileged information from individuals.



  • Extend offers to candidates without an extensive interview process with a member of our recruitment team and a hiring manager via video or in person.
  • Send job offers via email. All offers are first extended verbally by a member of our internal recruitment team whenever possible and then followed up via written communication.

All emails from Anaplan would come from an @anaplan.com email address. Should you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Anaplan, please send an email to before taking any further action in relation to the correspondence.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.