Senior Data Engineer (Multimodal Data and Entity Modelling)
First seen by Alion on Oct 2, 2026.
Are you passionate about safeguarding countries, societies, and businesses from hybrid threats?
Look no further! Our rapidly scaling company is committed to this crucial mission, collaborating with some of the world’s most influential organizations, including NATO and the EU.
If you’re ready to join a high-impact team shaping the future of intelligence and security, we invite you to become part of our journey. Join us and help defend the digital world with purpose and innovation!
Role Overview
We are looking for a Senior Data Engineer to work on the data architecture behind our intelligence platform, across both our production data infrastructure and our work with multimodal data.
We operate on text, social media, geospatial, and time-series data at scale. A large part of the engineering challenge is in how that data is represented and connected: the same real-world entity can be modelled on a map, as a node in a graph, and as a pattern over time, and the value comes from being able to query and reason across those views together.
You'll bring hands-on experience with geospatial data, knowledge graphs, or entity-relationship systems across multiple data types. We care more about how you reason through architectural and technology choices than about any specific tool.
This is a hands-on, senior role with real ownership over architecture, execution, and technical direction.
Key Responsibilities
Multimodal Data & Entity Modelling
Extract entities and relationships from text, social media, geospatial, and time-series data, and model them across map, graph, and temporal representations.
Evolve our knowledge graph layer and make connected data usable for analytics, visualisation, and AI agents.
Evaluate and prototype technologies for geospatial and graph workloads at scale
Core Data Platform
Migrate production workloads from PostgreSQL to StarRocks.
Improve ingestion and processing performance, and redesign product storage architecture for billion-row scale.
Own the infrastructure your pipelines run on, including deployment, performance, and cost.
Requirements
Hands-on experience building data systems for geospatial data, graph data, or knowledge graphs, ideally combining several data types.
Experience with GIS tooling (e.g. PostGIS), graph databases (e.g. Neo4j, TigerGraph), or modelling graph data on relational or columnar storage.
Strong architectural thinking and the ability to justify technology choices, run experiments, and change course based on results.
Proven experience moving and processing data at large scale, with resumable, idempotent, and memory-safe pipelines.
Experience working with data infrastructure beneath the managed layer, not only inside a ready-made SaaS platform.
Ability to read query plans and change physical data layout to fix performance issues.
Experience building and shipping production backend services in Python.
Comfort owning infrastructure, including Kubernetes, Helm, Terraform, or similar tools.
Fluent English.
Nice to Have
Production experience with a columnar or MPP engine such as StarRocks, Doris, ClickHouse, BigQuery, or Snowflake, including partitioning, distribution, and indexing.
Experience with Elasticsearch or OpenSearch at scale, including mappings, ILM, tiering, and reindexing.
Experience with a long-running migration involving dual-write, reconciliation, and cutover.
Knowledge of PostgreSQL internals.
Experience with event-driven ingestion using Kafka or RabbitMQ.
Experience with observability tools (Prometheus, Grafana, Loki), lakehouse formats (Parquet, Iceberg), and orchestrators such as Airflow.
Background in threat intelligence, OSINT, geospatial intelligence, or defence.
We Offer
Opportunity to contribute to a mission-driven startup and support prestigious clients, including governments worldwide, enterprise clients, and leading NGOs in tackling global security challenges.
Autonomy and freedom to drive experiments and bring your own ideas to life.
Flexibility of fully remote work.
Flexible, unlimited time-off policy.