Principal Software Architect (Graph Architect)

Role overview

Provide senior technical leadership for large scale software and data platforms, with a focus on resolving identities across diverse datasets. The work spans system architecture, hands on engineering guidance, and performance and reliability decisions for both batch processing and real time services.

Responsibilities

- Set architecture for identity matching, entity linking, deduplication, identity graphs, and lifecycle management. - Design systems that support high volume batch workloads and low latency APIs, including matching confidence, source prioritization, and record survivorship strategies. - Guide distributed applications and data pipelines using Java, Python, Scala, Apache Spark, SQL, AWS, Snowflake, and Databricks. - Establish patterns for data models, integrations, caching, concurrency, partitioning, security, observability, resiliency, and disaster recovery. - Review designs, diagnose performance and scalability issues, and help engineering teams turn architectural plans into maintainable implementations. - Mentor senior engineers and collaborate with product, data, security, infrastructure, and business stakeholders.

Requirements

- Bachelor’s degree in a relevant technical discipline or equivalent professional experience. - Deep practical expertise with Java, Python, Scala, Apache Spark, and SQL. - Experience designing large scale distributed systems, enterprise applications, APIs, and data processing platforms. - Strong knowledge of AWS and experience with Snowflake and Databricks. - Ability to evaluate architectural tradeoffs and guide teams on scalability, reliability, security, performance, and operational needs.

Nice to have

- Experience with graph databases or graph oriented data models, probabilistic or machine learning based matching, and advanced entity resolution. - Background in event driven or streaming systems, containerized workloads, infrastructure as code, or multi region cloud design. - Experience with large consumer, marketing, advertising, financial, or customer identity datasets; legacy platform modernization and architecture governance are also relevant.