
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Remote - United States"), this listing's salary midpoint is about 84% higher. The offer still falls within the benchmark range (€1,667–€20,050). The listed pay band (€16,866–€23,191) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 7 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Software Engineer | €3,500/per month | €5,750/per month | €12,307/per month |
| All roles in Remote - United States | €1,667/per month | €11,003/per month | €20,050/per month |
| From job ad (Mid-Level) | €16,866/per month | €20,029/per month | €23,191/per month |
We are seeking a Staff Software Engineer to join Reference and Entity Data Systems (REDS) and own the design and evolution of our entity data platform — ingesting company data from global vendors, resolving it into authoritative records, and delivering accurate, timely data to downstream teams and customers. REDS owns vendor ingestion, entity generation, data quality and freshness, and delivery to downstream consumers. If entity data is wrong, incomplete, or stale, everything downstream fails. Human validation still acts as a safety net in parts of the pipeline. Your mission is to systematically reduce that dependency by increasing correctness, confidence, and trust — without sacrificing speed or scale. You will operate at the intersection of distributed systems, entity resolution, data quality, AI-assisted decision-making, and platform architecture. Who You Are: - 8+ years building and operating large-scale production systems - Proven experience with data ingestion, entity resolution, matching, or normalization at scale - Deep expertise in one or more of: distributed systems, data pipelines, reference data platforms, platform engineering, or AI-powered classification and validation - Strong code, system design, and architecture pattern skills - Ability to design trustworthy systems combining probabilistic (AI) and deterministic approaches - Delivery excellence: incident response, observability, and reliability improvements that stick - Effective use of AI, testing, automation, and tooling to ship confidently - Track record of setting standards, driving technical decisions, and elevating peers through documentation and mentoring - End-to-end ownership from integration through entity generation to operational readiness - Experience with company or financial reference data, or vendor reconciliation (preferred) - Provenance, lineage, confidence-scoring, or quarantine/resolution workflows (preferred) - Integrating new data vendors end to end (preferred) - Cloud-native architectures and internal platforms shared across teams (preferred) What You’ll Do: - Own the architecture and evolution of a major area of the entity data platform - Design systems that process large volumes of heterogeneous vendor data with high reliability, freshness, and accuracy - Reduce manual validation overhead through AI-assisted resolution, confidence scoring, provenance, and deterministic matching rules - Establish clear contracts for correctness and traceability — e.g., which source supplied a field, why an entity was matched or created - Balance AI-driven and rules-based approaches where each improves reliability and explainability - Deliver end-to-end integrations across ingestion, matching, entity generation, and delivery - Respond to production incidents in your area; improve observability and reliability through iterative hardening - Set engineering standards, mentor engineers, and partner with product and downstream consumers on quality bars and success metrics
Job Details
Responsibilities
- Own the architecture and evolution of a major area of the entity data platform
- Design systems for processing large volumes of heterogeneous vendor data with high reliability and accuracy
- Reduce manual validation overhead through AI-assisted resolution and deterministic matching rules
- Establish contracts for correctness and traceability of data sources
- Balance AI-driven and rules-based approaches for reliability and explainability
- Deliver end-to-end integrations across ingestion, matching, and delivery
- Respond to production incidents and improve observability
- Set engineering standards and mentor engineers
Requirements
- 8+ years building and operating large-scale production systems
- Proven experience with data ingestion, entity resolution, matching, or normalization at scale
- Deep expertise in distributed systems, data pipelines, reference data platforms, platform engineering, or AI-powered classification and validation
- Strong code, system design, and architecture pattern skills
- Ability to design trustworthy systems combining probabilistic (AI) and deterministic approaches
- Experience with incident response, observability, and reliability improvements
- Track record of setting standards and mentoring peers
Skills & Technologies
Benefits & Perks

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