We are looking for brilliant engineers to join our team at Magentic. We’re pushing the boundaries of AI with next-generation agentic systems that can manage entire workflows. We’re focusing on a three trillion dollar market of supply chains and procurement.
Our mission is to make global manufacturing supply chains robust to an ever-changing world, and to harness the potential of generative AI through thoughtful deployment, maximising benefits while prioritising ethical use and safety.
Data Engineers are the backbone of Magentic. They design, build, and maintain the scalable data infrastructure that powers our intelligent agentic systems. You’ll work closely with ML engineers, product teams, and domain experts to transform raw supply chain data into structured, reliable, and actionable insights that drive decision-making across our platform.
We’re creating the data foundation for autonomous agents to reason, plan, and act in complex, high-stakes environments. This role is an opportunity to work on deeply technical challenges with real-world impact at scale.
Tasks
In this role, you will:
- Design and operate performant, scalable ingestion pipelinesprocessing high-volume data from global supply chain and procurement systems.
- Define, evolve, and manage data schemas and catalogues—from raw staging to high-quality analytics and feature stores—ensuring consistency and discoverability.
- Build end-to-end monitoring and observabilityfor your pipelines: owning data quality, latency, completeness, and lineage at every stage.
- Champion secure, governed data practices: access controls, secrets management, encrypted data-in-transit/at-rest, and compliance with frameworks like GDPR.
- Collaborate closely with AI, Platform, and Product teams, provisioning data sets, feature tables, and contracts for analytics and machine learning at scale.
- Continuously improve efficiency and reliabilityvia testing, CI/CD automation, cost/performance tuning, and incident/root-cause reviews.
Requirements
You may be a fit if you have:
- Expertise in Cloud-Native Data Engineering:3+ years building and running data pipelines in AWS or Azure, including managed data services (e.g., Kinesis, EMR/Databricks, Redshift, Glue, Azure Data Lake).
- Programming Mastery:Advanced skills in Python or another major language; writing clean, testable, production-grade ETL code at scale.
- Modern Data Pipelines:Experience with batch and streaming frameworks (e.g., Apache Spark, Flink, Kafka Streams, Beam), including orchestration via Airflow, Prefect or Dagster.
- Data Modeling & Schema Management:Demonstrated expertise in designing, evolving, and documenting schemas (OLAP/OLTP, dimensional, star/snowflake, CDC), data contracts, and data cataloguing.
- API & Integration Fluency:Building data ingestion from REST/gRPC APIs, file drops, message queues (SQS, Kafka), and 3rd party SaaS integrations, with idempotency and error handling.
- Storage & Query Engines:Strong with RDBMS (PostgreSQL, MySQL), NoSQL (DynamoDB, Cassandra), data lakes (Parquet, ORC), and warehouse paradigms.
- Observability & Quality:Deep familiarity with metrics, logging, tracing, and data quality tools (e.g., Great Expectations, Monte Carlo, custom validation/test suites).
- Security & Governance:Data encryption, secrets management, RBAC/ABAC, and compliance awareness (GDPR, CCPA).
- CI/CD for Data Systems:Comfort with automation, infrastructure as code (Terraform), version control, and release workflows.
- Collaborative Spirit:Experience working closely with platform, ML, and analytics teams in a fast-paced, mission-driven environment.
Benefits
Compensation and Benefits
At Magentic, we recognise and reward the talent that drives our success. We offer:
- Competitive Equity: play a real part in Magentic’s upside.
- A salary of £110,000-£120,000
- Visa sponsorshipavailable; we prioritise UK-based candidates but welcome global talent.
- Hybrid London HQ(3-4 days in the office) with remote flexibility.
- Annual team retreat—a fully-funded off-site to recharge, bond, and build.
About Magentic
At Magentic, we are committed to developing artificial intelligence that benefits humanity. We push the limits of AI's capabilities and are dedicated to its responsible and safe deployment. Recognising the profound impact of AI, we ensure that its development is centred around human needs and safety, incorporating a wide array of perspectives to fulfil our mission. We bring expertise from OpenAI, NASA, and McKinsey, and we’re backed by the best venture funds in the world.
We can’t wait to have you on board.
Equal Opportunities Statement
Magentic is committed to creating a diverse and inclusive workplace and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender reassignment, marital or civil partnership status, age, disability, pregnancy or maternity, or any other basis as protected by the Equality Act 2010.
We actively encourage applications from candidates of all backgrounds and cultures and believe a diverse workforce enhances our ability to deliver innovative solutions. We also ensure that our employment decisions are based solely on individual qualifications, merit, and business needs.
Accommodations for Applicants with Disabilities
Magentic is dedicated to providing reasonable accommodations to job applicants with disabilities. If you require any adjustments during the recruitment process, please indicate this in your application or contact us directly
We’re building autonomous teammates for the supply chain and procurement teams that keep the world moving.
Supply‑chain and procurement teams run on grit and spreadsheets. Their days disappear inside labyrinthine ERP systems, while price shocks, regulatory twists, and sustainability targets pile on. We’ve felt that grind first‑hand, and we knew there had to be a better way.
Supply chains are the hidden engines of our world—complex, fragile, and too often overlooked until they break. We started Magentic when the world ran out of the medications that kept our families alive. That crisis drove us to build a technology that doesn’t just keep up—it stays miles ahead.
