Principal Data Engineer

Anaplan; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Anaplan is seeking a Principal Data Engineer to shape the data platform across ingestion, transformation, storage, and governance at scale. You will build high‑throughput pipelines powering AI initiatives and analytics, enabling business users to act on massive datasets in planning workflows.

You will lead architecture and implementation of data lakes, warehouses, vector databases, and streaming systems, partnering with analytics, product, and platform teams to deliver reliable, scalable data

Qualifications

• Extensive data engineering experience in complex data environments.
• Hands-on with AI/data platforms and scalable pipelines.
• Experience with distributed processing and cloud data warehouses.

Responsibilities

• 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.

Skills

Big Data concepts

Data modeling

Python

SQL

Distributed computing

Data governance

Data pipelines

ETL/ELT design

Tools

Apache Spark

Apache Flink

Apache Kafka

Kinesis

Airflow

Dagster

Snowflake

BigQuery

Redshift

Databricks

Delta Lake

Iceberg

Job description

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 celebratingour 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!

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 (e.g., Apache Spark, Flink, Hadoop).
• Strong expertise in message brokers and event streaming platforms (e.g., Apache Kafka, Kinesis).
• End‑to‑end exposure to data pipeline lifecycle development, including extensive experience with workflow orchestration tools (e.g., Apache Airflow, Dagster).
• Hands‑on expertise with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lake architectures (e.g., Databricks, Delta Lake, Apache Iceberg).
• 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, Inclusionand 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.