Senior Data Architect

PeakMetrics is a narrative intelligence platform that protects enterprises and government agencies from social media manipulation, influence campaigns, and emerging narrative threats. Using advanced machine learning, our platform transforms millions of cross-channel media signals into actionable intelligence — giving customers the context and clarity they need to detect threats early and respond effectively. The Role As a Senior Data Architect, you will own the design and evolution of PeakMetrics’ data systems. You will work closely with engineering and product teams to ensure our data architecture supports real-time processing, analytics, and machine learning use cases without relying on a dedicated Data Scientist role. The right candidate is hands-on, systems-oriented, and able to apply data science principles to what they build. You will report directly to the Vice President of Engineering. Key Responsibilities at PeakMetrics: - Share ownership and evolve the end-to-end data architecture across streaming, batch, and analytical workloads - Design data models that preserve signal from unstructured and semi-structured sources - Enable machine learning workflows by defining clear contracts between raw, derived, and model-ready data - Establish standards for schema evolution, dataset versioning, reproducibility, and data quality - Partner closely with engineering teams to improve scalability, reliability, and cost efficiency - Embed applied data science considerations into architectural decisions, including feature reuse, temporal consistency, and leakage prevention - Document and communicate architectural decisions clearly across teams We would love to hear from you if: - You have eight or more years of experience working with production data systems - You have designed data architectures, not just individual pipelines - You have strong experience with streaming platforms such as Kafka or AWS Kinesis (Preferred) - You have experience with data orchestration tools such as Temporal (Preferred), Dagster or Airflow - You have experience with cloud-native data stacks, AWS preferred - You understand data modeling for analytics and machine learning use cases - You have working knowledge of machine learning workflows and feature engineering concepts - You have experience training AI Models and testing models for domain optimization - You are fluent in SQL and Python - You communicate clearly and collaborate effectively across teams in a remote environment It would be nice if you had: - Experience supporting NLP or narrative intelligence systems - Familiarity with Athena, Parquet, Iceberg, or similar analytical storage technologies - Experience designing data systems for noisy or adversarial data environments - Experience supporting the data needs of machine learning teams Benefits - Remote-first culture - Competitive Compensation - Health insurance, 401(k) and other benefits - Flexible work schedule and unlimited time off - Opportunities for professional growth and development - A vibrant and inclusive company culture PeakMetrics is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status.