Principal Data Architect

Babel Street is hiring a hands-on Principal Data Architect for Data Platform and Pipelines to redesign and rebuild the company's data infrastructure and pipelines, set the target architecture, write critical code, and lead engineers through a multi-year move of a petabyte-scale platform onto Google Cloud. This is a principal engineering role, not a people-management role. The role reports to the SVP of Engineering and works alongside the Head of Architecture, AI, Graph and Product teams.

Responsibilities

Map the current data estate end to end and publish a target-state data architecture and sequenced migration plan within the first 90 days; Design and build the new ingestion and processing backbone with a standard pattern for streaming and batch ingestion, enrichment, and delivery; Lead the data platform workstream of the GCP migration, deciding what moves as is, what gets rebuilt, and what gets retired; Rationalize storage and search across warehouse, search, object, vector and graph stores, and cut the cost of the most expensive workloads; Build the data foundation for AI, including agent-callable data services, hybrid retrieval, and provenance and lineage on every record; Build the governance and compliance platform for governed and compliant data; Make the platform operable with data contracts, quality checks, observability and cost attribution; Own pipelines, storage, cloud migration, retrieval and AI enablement, data quality and economics; Provide technical leadership through architecture decision records, design reviews, coding standards, mentoring senior engineers, partnering with offshore engineering teams, and serving as escalation point for the hardest data incidents

Requirements

12+ years building data systems, with at least 5 as the lead architect or principal engineer on a large-scale data platform; Production code experience with strong Python plus at least one of Java, Scala or Go, and fluent SQL; Personally led a major re-architecture or cloud migration of a data platform; Deep hands-on experience with distributed processing and streaming (e.g., Spark, Beam/Dataflow, Flink, Kafka, Pub/Sub or Pulsar); Production experience with GCP data services such as BigQuery, Dataflow, Pub/Sub, GCS and Spanner; AWS experience; Expert-level operation of search and index systems (Elasticsearch or OpenSearch) at scale; Experience with lakehouse table formats (Iceberg, Delta or Hudi) and orchestration (Airflow/Composer, Dagster or similar); Track record of cutting platform cost materially without hurting performance; Clear written communication; Ability to obtain a US security clearance; Bachelor's degree in Computer Science, Engineering or a related technical field, or equivalent hands-on experience

Nice to have

Experience with vector search, embeddings pipelines and retrieval architectures for LLM and agentic applications; Experience with entity resolution, knowledge graphs or graph databases, ideally across multilingual or messy real-world data; Background in OSINT, national security or law enforcement, risk intelligence, and financial data; Experience building for FedRAMP, IL5 or air-gapped environments, including running data platforms without managed cloud services; Experience with data observability, lineage and governance tooling (e.g., OpenLineage, Great Expectations, Monte Carlo, Dataplex); Experience combining large volumes of scraped multimedia and structured third-party data; A Master's or PhD is a plus

Benefits

Health benefits covering 85-100% of monthly premium costs for Medical, Dental, Vision, Life & Disability insurance for employee and family; Traditional and Roth 401(K) with a very competitive match; Unlimited flexible leave; 12 paid Federal Holidays; Tuition Reimbursement Program