Senior Data Architect

PeakMetrics

1d•Remote

About The Position

At PeakMetrics, we stand at the forefront of narrative intelligence, harnessing the power of advanced machine learning to safeguard enterprises and government agencies from social media manipulation and narrative attacks. Our platform rapidly sifts through millions of unstructured, cross-channel media datasets, transforming them into actionable insights. By identifying adversarial online messaging, understanding its audience, and providing crucial context such as source credibility, we empower our customers to effectively respond to digital threats. Our team tackled some of today's most intricate media challenges, from crisis management to thwarting state-sponsored influence campaigns. Our goal is unwavering: to shield our clients from the risks of social media manipulation and emerging narrative threats by detecting and remediating from harmful online trends. 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.

Requirements

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

Nice To Haves

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

Responsibilities

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