Principal Software Architect (Graph Architect)

We are seeking a highly experienced Principal Software Architect to provide technical leadership and architectural direction across complex, high-scale software and data platforms.

This role will have a particular focus on Identity Resolution, including the design of systems that accurately identify, match, link, and resolve individuals, households, organizations, devices, and other entities across large and diverse datasets. In addition to Identity Resolution, the Principal Software Architect will be responsible for designing scalable enterprise applications, distributed systems, large-scale data-processing platforms, and low-latency APIs and services.

The ideal candidate will have deep, hands-on expertise across Java, Python, Scala, Apache Spark, and SQL, with strong experience designing systems on AWS, Snowflake, and Databricks.

This is a senior technical leadership role requiring the ability to define architectural direction, evaluate technology choices, solve complex engineering challenges, and work closely with engineering teams to ensure solutions are scalable, reliable, secure, maintainable, and performant.

Key Responsibilities

• Define and drive the architecture for enterprise-scale Identity Resolution platforms and services.

• Design systems for deterministic and probabilistic identity matching, entity resolution, identity graphs, record linkage, deduplication, and identity consolidation.

• Develop architectures capable of resolving identities across large, diverse, and rapidly changing datasets.

• Design solutions supporting both real-time and batch Identity Resolution use cases.

• Define strategies for identity matching, confidence scoring, survivorship, source prioritization, identity linking, and identity lifecycle management.

• Design and optimize low-latency APIs and services capable of supporting high-throughput, highly available production workloads.

• Architect distributed applications and services using Java, Python, and Scala, selecting the appropriate language and framework based on workload and system requirements.

• Design high-scale data-processing pipelines and platforms using Apache Spark, including Spark workloads implemented in Scala and Python.

• Design and optimize data solutions using Snowflake and Databricks for large-scale analytical and operational workloads.

• Design highly efficient data models and SQL-based solutions supporting transactional, analytical, and Identity Resolution workloads.

• Define appropriate caching, concurrency, partitioning, indexing, persistence, and data-access strategies to meet stringent performance and latency requirements.