At a Glance
- Tasks: Lead the design and deployment of scalable data systems for AI infrastructure.
- Company: Join Anaplan, a leader in AI-infused business planning solutions.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Diverse team committed to innovation and celebrating successes.
- Why this job: Make a real impact by optimising data for top global companies.
- Qualifications: Extensive data engineering experience and strong software skills required.
The predicted salary is between 75600 - 92400 £ per year.
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. 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. 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.
About the Role
We're seeking a Principal Data Engineer who can work across the full stack of Anaplan's data platform, setting the technical direction for how we ingest, transform, store, serve, and govern data at scale. You will build highly performant, robust data pipelines that process massive volumes of data in real-time and batch. This foundational work empowers business users to leverage vast datasets in their planning workflows and forms the bedrock for our advanced analytics and AI initiatives. You'll need deep knowledge of distributed computing, data architecture, and strong software engineering skills to tackle complex, high-scale data challenges.
Your Impact
- Lead the data architecture, design, and deployment of scalable, high-throughput Big Data systems into production environments.
- Architect, deploy, and manage the foundational data systems that underlie modern AI infrastructure, including vector, NoSQL, and document databases.
- Develop end-to-end data engineering solutions, including robust ETL/ELT pipelines, API services, and data ingestion frameworks.
- Design and build the storage and processing layers powering our analytics workloads: data lakes, data warehouses, distributed file systems, and real-time streaming architectures.
- Engineer feature-rich context pipelines that process large-scale enterprise data, balancing batch and streaming patterns seamlessly.
- Optimise and scale large distributed queries and data transformations to ensure high performance and low latency for end users.
- Implement data quality frameworks to measure and ensure data integrity, reliability, and governance across all data assets.
- Collaborate with analytics, product, and platform teams to build data models that capture the semantics of customer metrics, hierarchies, and relationships.
- Stay current with the modern data stack and big data landscape, evaluating new tools, distributed computing frameworks, and database technologies for potential adoption.
Your Skills
- Extensive data engineering experience, demonstrating a strong track record of hands-on execution and delivery in complex data environments.
- Deep practical understanding of the database ecosystems that power AI and machine learning infrastructure (e.g., Vector databases, NoSQL, and Document stores).
- Hands-on experience building, scaling, and shipping large-scale data platforms in production.
- Deep practical experience with distributed data processing frameworks.
- End-to-end exposure to data pipeline lifecycle development, including extensive experience with workflow orchestration tools.
- Hands-on expertise with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lake architectures.
- Advanced SQL skills and proficiency in Python.
- Strong background in modern software development practices (testing, code review, CI/CD, Infrastructure as Code).
Desirable
- Extensive, progressive experience leading technical projects and mentoring engineering teams.
- Hands-on experience with cloud-native infrastructure (AWS, GCP, or Azure).
- Experience implementing data observability, monitoring, and alerting frameworks at scale.
- Familiarity with Anaplan or similar enterprise planning platforms.
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. 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 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.
Principal Data Engineer - Aws in London employer: Anaplan
Anaplan in Manchester is an exceptional employer that prioritises diversity, equity, and inclusion, fostering a collaborative work culture where every voice is valued. Employees benefit from continuous growth opportunities through professional development and access to cutting-edge BI tools, making it an ideal environment for those looking to make a meaningful impact in the field of data analytics.
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We think this is how you could land Principal Data Engineer - Aws in London
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We think you need these skills to ace Principal Data Engineer - Aws in London
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Anaplan. 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 Anaplan
✨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!
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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
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✨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.
