Backed by global technology visionaries like Sequoia Capital, Magentic brings together world-class AI engineering (formers from OpenAI, Meta, and AWS) with procurement expertise (formers from McKinsey & Company and ABInBev).
We are looking for a brilliant Data Engineer 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.
In this role, you will:
* Design and operate performant, scalable ingestion pipelines
processing 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 observability
for 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 reliability
via testing, CI/CD automation, cost/performance tuning, and incident/root-cause reviews.
What we're looking for:
* 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.
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 sponsorship
available; (note we are only accepting candidates who are currently based in the UK.)
* Hybrid London HQ
(3-4 days in the office)
* Annual team retreat
—a fully-funded off-site to recharge, bond, and build
Our interview Process
We run a lightweight interview process of three stages. These are:
1. Initial candidate screening
(30 mins)
: this first step is an opportunity for us to learn more about your goals, interests, and how they align with the role.
2. Design interview with the CTO (45 mins):
in this step, we present you with real problems Magentic encounters, and we ask you to design a solution in a whiteboarding exercise.
3. In-person interview (half-day, paid):
for the final step, we invite you to come meet the team in-person and work alongside us We find this is the best way for candidates to get a sense of what working at Magentic is like.