data engineer in AdTech

TREQS develops AdTech software focused on identity resolution, cross-surface reach, user-level measurement, lower-funnel attribution, and in-app inventory.

• Build a new identity graph covering identifier sync, translation, clustering with Data Science, and opt-out handling;
• Standardize partner and client onboarding across web, CTV, and mobile identifiers, including cleanroom onboarding;
• Prepare the identity audience layer for self-serve creation, activation, state management, and reporting;
• Own observability and alerting by consolidating signals, setting freshness and quality standards, enabling AI-assisted triage, and writing runbooks;
• Lead and grow the data engineering team through standards, code review, mentoring, and ADRs.

• Proven ownership of large-scale, interdependent data systems, including one built from scratch;
• Ability to turn ambiguity into a roadmap with Product and Partnerships teams;
• Engineering leadership experience in setting direction, reviewing work, and developing people while staying hands-on;
• Mastery of Python, Airflow, Spark, and SQL with Snowflake, focused on cost, performance, and testability;
• Strong AWS, Kubernetes, infrastructure log diagnostics, and third-party API ingestion skills;
• Fluency with AI tooling and codebase legibility for it;
• Nice to have: Identity resolution or graph work in AdTech, privacy and consent expertise including GDPR, CCPA, opt-outs, and deletion, data cleanroom experience, CI/CD with GitHub Actions or ArgoCD, monitoring with VictoriaMetrics, Prometheus, or Grafana, Iceberg, streaming with Kafka or Redpanda, low-latency stores such as Aerospike, OLAP with ClickHouse.

• Remote from anywhere in Europe or UK;
• Bonus and benefits.