Senior Data Platform Architect & Tech Leader

Early Warning; New York (NY); Hybrid; USD 207,000 - 276,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Match

Paid Time Off

Paid Parental Leave

Maven Family Planning

Job summary

Early Warning is seeking a hands-on Principal Engineer to shape architecture and engineering direction for enterprise data platforms and data products. You will lead across Data Exchange, Data Products, data engineering, and cloud capabilities to ensure scalable ingestion, transformation, modeling, quality, governance, and consumption.

Partner with Product, Engineering, Security, and Data teams to translate business needs into pragmatic architecture, modernize legacy capabilities, and accelerate

Qualifications

• Bachelor’s degree in Computer Science or related field.
• 15 years of experience in software with 8+ in FinTech.
• Experience leading cross-functional technical initiatives.
• Hands-on experience with Databricks, Spark/PySpark, Kafka, Snowflake, Python.

Responsibilities

• Owns technical product design and architecture for enterprise data platforms and cloud capabilities.
• Shapes target-state and transition architectures for modernization.
• Translates product strategy into data capabilities and roadmaps.
• Establishes reusable engineering patterns, data contracts, and domain models.
• Leads modernization of legacy data capabilities to cloud-based architectures.
• Mentors engineers and communicates complex technical concepts.

Skills

Cross-functional leadership

SDLC best practices

Agile/LEAN/Scrum

DevOps practices

Communication

Architectural thinking

Hands-on data engineering

Education

Bachelor’s degree in Computer Science

Tools

Databricks

Spark/PySpark

Kafka

Snowflake

Cloud platforms (AWS/Azure/GCP)

Relational/NoSQL databases

Python

Job description

Early Warning is seeking a hands-on Principal Engineer to shape architecture and engineering direction for enterprise data platforms and data products. You will lead across Data Exchange, Data Products, data engineering, and cloud capabilities to ensure scalable ingestion, transformation, modeling, quality, governance, and consumption.

Partner with Product, Engineering, Security, and Data teams to translate business needs into pragmatic architecture, modernize legacy capabilities, and accelerate