Principal Data Architect

Hatch IT • Reston, VA

2d • $220,000 - $250,000

About The Position

Babel Street is seeking a hands-on Principal Data Architect to redesign and rebuild its data infrastructure and pipelines. The architect will define the target architecture, write critical production code, and lead engineers through a multi-year migration of a petabyte-scale data platform to Google Cloud. The platform supports data collected, enriched, and resolved across hundreds of sources and dozens of languages. The role will replace disparate warehouse, search, object-storage, and legacy delivery systems with a coherent, cost-effective, reliable platform designed for AI and agentic workloads.

This is a principal engineering role rather than a people-management position. Success will be measured by the systems designed and shipped, the quality of technical decisions, and the architect’s impact on engineering standards. The position reports to the SVP of Engineering and works alongside the Head of Architecture and the AI, Graph, and Product teams.

During the first year, the architect will map the current data estate and publish a target architecture and sequenced migration plan; design and build a standard ingestion and processing backbone; lead the data-platform workstream of the AWS-to-GCP migration; rationalize storage and search; deliver AI-ready data services, hybrid retrieval, provenance, and lineage; establish governance and compliance capabilities; and improve platform operations through data contracts, quality checks, observability, SLOs, and cost attribution.

The architect owns the architecture and reference implementations for ingestion, processing, enrichment, and delivery; the physical data platform across warehouse, lakehouse, search, and object storage; technical designs for cloud migration and specialized deployment environments; retrieval and query capabilities for analysts and AI agents; data quality, lineage, observability, and platform economics; and technical leadership through design reviews, standards, mentoring, and incident escalation.

Requirements

• 12+ years building data systems, including at least 5 years as lead architect or principal engineer on a large-scale data platform.
• Continues to write production code; strong Python skills, proficiency in at least one of Java, Scala, or Go, and fluency in SQL.
• Personally led a major data-platform re-architecture or cloud migration and can explain its design, sequencing, challenges, and lessons learned.
• Deep hands-on experience with distributed processing and streaming technologies such as 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, as the platform is being migrated from AWS.
• Expert-level experience operating Elasticsearch or OpenSearch at scale, including cluster sizing, mappings, aggregation performance, and cost tuning.
• Experience with lakehouse table formats such as Iceberg, Delta, or Hudi, and orchestration tools such as Airflow/Composer, Dagster, or similar.
• Demonstrated success materially reducing platform costs without harming performance, supported by measurable results.
• Clear written communication and ability to write design documents understandable to both executives and senior engineers.
• Ability to obtain a U.S. security clearance.

Nice To Haves

• Experience with vector search, embeddings pipelines, and retrieval architectures for LLM and agentic applications.
• Experience with entity resolution, knowledge graphs, or graph databases, ideally involving multilingual or messy real-world data.
• Background in OSINT, national security, law enforcement, risk intelligence, or financial data.
• Experience building for FedRAMP, IL5, or air-gapped environments, including operating data platforms without managed cloud services.
• Experience with data observability, lineage, and governance tools such as OpenLineage, Great Expectations, Monte Carlo, or Dataplex.
• Experience combining large volumes of scraped multimedia and structured third-party data.

Responsibilities

• Map the existing data estate end to end, including sources, pipelines, stores, consumers, delivery paths, volume, cost, ownership, and failure history.
• Publish a target-state data architecture and sequenced migration plan for engineering and product leadership approval.
• Design and build a standard backbone for streaming and batch ingestion, enrichment, processing, and delivery, supporting millions of documents per day with clear SLOs.
• Lead the data-platform workstream of the AWS-to-GCP migration, deciding what to migrate, rebuild, or retire and owning technical designs for each migration wave.
• Rationalize warehouse, search and index, object, vector, and graph storage; define appropriate use patterns and consolidate workloads to reduce costs.
• Build AI-ready data services callable by agents, hybrid retrieval across keyword, analytical, vector, and graph data, and record-level provenance and lineage.
• Build a governance and compliance platform that centralizes and serves governed data, including privacy-related parameters, exclusions, and retention.
• Establish data contracts, automated quality checks, observability, SLOs, ownership, and cost attribution for pipelines.
• Define architecture and reference implementations for collection, ingestion, parsing, enrichment, and delivery, including translation, named-entity recognition, and entity resolution.
• Design event-driven and queue-based processing, idempotency, backfills and replay, schema evolution, and exactly-once or effectively-once guarantees where needed.
• Own the physical data platform across warehouse, lakehouse, search, and object storage, including petabyte-scale partitioning, indexing, tiering, retention, query and aggregation performance, and hardware and cost trade-offs.
• Design data-workload migration from AWS to GCP with minimal customer disruption, using patterns that can also support FedRAMP, disconnected, and air-gapped deployments.
• Build APIs and query layers for analysts and agents and partner with AI and Graph teams on retrieval supporting RAG and agentic workflows.
• Track platform unit economics, including cost per source, pipeline, query, and customer.
• Write architecture decision records, lead design reviews, and establish data-engineering coding standards.
• Mentor senior engineers, partner with offshore engineering teams, and serve as the escalation point for the most difficult data incidents.
• Write production code and communicate technical designs clearly to both executive and engineering audiences.

Benefits

• Medical, dental, vision, life, and disability insurance, with Babel Street covering 85–100% of monthly premiums for employees and their families.
• Traditional and Roth 401(k) plans with a competitive match.
• Unlimited flexible leave.
• 12 paid federal holidays.
• Tuition reimbursement for continuing education.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed