{"id":3466857,"url":"https://alion.io/job/osavul-senior-data-engineer-multimodal-data-and-entity-modelling","title":"Senior Data Engineer (Multimodal Data and Entity Modelling)","company":{"id":181308,"name":"Osavul","domain":"osavul.cloud","url":"https://alion.io/company/osavul","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["UA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":63000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2679},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Helm","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Kubernetes","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Neo4j","optional":false},{"name":"PostGIS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"StarRocks","optional":false},{"name":"Terraform","optional":false},{"name":"Time Series","optional":false},{"name":"Apache Kafka","optional":true},{"name":"ClickHouse","optional":true},{"name":"ElasticSearch","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Grafana","optional":true},{"name":"Loki","optional":true},{"name":"OpenSearch","optional":true},{"name":"Prometheus","optional":true},{"name":"RabbitMQ","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-10-02T19:28:34Z","employer_posted_date":null,"last_verified_at":"2026-10-02T19:28:34Z","board_verified":false,"closed_at":null,"days_open":30,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":30},"description":"Are you passionate about safeguarding countries, societies, and businesses from hybrid threats?\nLook 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.\nIf 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!\n\nRole Overview\n\nWe 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.\nWe 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.\nYou'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.\nThis is a hands-on, senior role with real ownership over architecture, execution, and technical direction.\n\nKey Responsibilities\n\nMultimodal Data & Entity Modelling\n\nExtract entities and relationships from text, social media, geospatial, and time-series data, and model them across map, graph, and temporal representations.\n\nEvolve our knowledge graph layer and make connected data usable for analytics, visualisation, and AI agents.\n\nEvaluate and prototype technologies for geospatial and graph workloads at scale\n\nCore Data Platform\n\nMigrate production workloads from PostgreSQL to StarRocks.\n\nImprove ingestion and processing performance, and redesign product storage architecture for billion-row scale.\n\nOwn the infrastructure your pipelines run on, including deployment, performance, and cost.\n\nRequirements\n\nHands-on experience building data systems for geospatial data, graph data, or knowledge graphs, ideally combining several data types.\n\nExperience with GIS tooling (e.g. PostGIS), graph databases (e.g. Neo4j, TigerGraph), or modelling graph data on relational or columnar storage.\n\nStrong architectural thinking and the ability to justify technology choices, run experiments, and change course based on results.\n\nProven experience moving and processing data at large scale, with resumable, idempotent, and memory-safe pipelines.\n\nExperience working with data infrastructure beneath the managed layer, not only inside a ready-made SaaS platform.\n\nAbility to read query plans and change physical data layout to fix performance issues.\n\nExperience building and shipping production backend services in Python.\n\nComfort owning infrastructure, including Kubernetes, Helm, Terraform, or similar tools.\n\nFluent English.\n\nNice to Have\n\nProduction experience with a columnar or MPP engine such as StarRocks, Doris, ClickHouse, BigQuery, or Snowflake, including partitioning, distribution, and indexing.\n\nExperience with Elasticsearch or OpenSearch at scale, including mappings, ILM, tiering, and reindexing.\n\nExperience with a long-running migration involving dual-write, reconciliation, and cutover.\n\nKnowledge of PostgreSQL internals.\n\nExperience with event-driven ingestion using Kafka or RabbitMQ.\n\nExperience with observability tools (Prometheus, Grafana, Loki), lakehouse formats (Parquet, Iceberg), and orchestrators such as Airflow.\n\nBackground in threat intelligence, OSINT, geospatial intelligence, or defence.\n\nWe Offer\n\nOpportunity to contribute to a mission-driven startup and support prestigious clients, including governments worldwide, enterprise clients, and leading NGOs in tackling global security challenges.\n\nAutonomy and freedom to drive experiments and bring your own ideas to life.\n\nFlexibility of fully remote work.\n\nFlexible, unlimited time-off 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