Senior Data Engineer

Tadaweb is a pioneering technology company with roots in Luxembourg and a growing global presence, with offices in the United Kingdom, France, and the United States. For over 13 years, we’ve been on a mission to make the world a safer place by empowering analysts with the tools they need to access the right information at the right time. Our cutting-edge SaaS platform revolutionizes PAI and OSINT investigations, making them faster, smarter, and more effective, all while adhering to the highest ethical standards by relying solely on publicly available information and supporting our clients’ policies. Renowned for our “nothing is impossible” ethos, we prioritize trust, transparency, and innovation in everything we do. Tadaweb builds software for PAI (Publicly Available Information) and OSINT (Open-Source Intelligence) analysts. We are looking for a Senior Data Engineer to play a key role in our production data pipelines and platform. You will join our Data Team and work with ML engineers, data scientists and product teams. What You Will Work On: We use a medallion architecture. Raw data from many external sources lands in a bronze layer. This is then loaded into a document store, a geospatial store and a graph database on Spanner. Data quality checks and entity resolution run along the way. The platform runs on Google Cloud. The core code is written in Go and Python. Your Impact:
• Pipelines: build, run and monitor pipelines from ingest to the serving stores. Handle backfills and reprocessing.
• New sources: add new external sources, including web, multilingual and geospatial data. Handle schema changes, duplicates and gaps.
• Structuring and loading: extend the structuring services. Design how entities are stored in the document, geospatial and graph stores.
• Location data: parse, clean and geocode addresses and place names in several languages. Link locations to entities and events.
• Data quality: write checks that stop bad data before it reaches users. Track data quality with metrics.
• Entity resolution: build and tune record matching across sources. Measure precision and recall.
• Migration: move data from legacy systems to the new platform, with rollback and data integrity checks.
• Team: set standards for testing, documentation and code review. Compare tools before choosing one. Turn requirements from analysts and product teams into technical designs. Mentor other engineers. What You Will Bring:
• 5+ years as a data engineer, including running production pipelines.
• Strong Python or Go, and SQL. Testing, code review and CI/CD as normal practice.
• Data modelling across different stores: relational, document, graph or geospatial.
• Geospatial basics: coordinate reference systems, reprojection, spatial joins and spatial indexes.
• Experience matching or deduplicating records from different sources.
• Cloud data services, ideally Google Cloud (BigQuery, Pub/Sub, Spanner).
• Orchestration and containers (Docker, Kubernetes).
• Able to work on unclear problems on your own and give reliable estimates.
• A degree in computer science, engineering or a related field, or equivalent experience.
• Fluent English. You get bonus points if you have any of the following:
• Both Python and Go.
• Entity resolution tools such as Splink or Senzing.
• Graph databases: Spanner Graph, Neo4j, GQL or Cypher.
• Geospatial tools: PostGIS, GeoPandas, shapely, GDAL, BigQuery GIS.
• Address data: libpostal, Nominatim, OpenStreetMap or GeoNames.
• Elasticsearch, OpenSearch or MongoDB.
• Microservices and messaging (REST, gRPC, RabbitMQ).
• Running ML models inside pipelines.
• Work in OSINT, defence, KYC (Know Your Customer), AML (Anti-Money Laundering), maritime or other regulated areas, building data solutions with compliance in mind.
• Modern Python tooling (uv, ruff, pytest) and AI coding tools such as Claude Code. Our offer:
• The opportunity to join a growing tech company, with strong product-market fit and an ambitious roadmap.
• The chance to join a human-focused company that genuinely cares about its employees and core values.
• A focus on performance of the team, not hours at the desk.