Senior Analytics Platform Engineer — AI Insurance SaaS

EvolutionIQ, Inc.; New York (NY); On-site; USD 200,000 - 225,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401k matching

Parental leave

Job summary

EvolutionIQ, Inc. in New York, NY seeks a Senior Analytics Engineer to design and scale a next‑generation analytical data platform.

You will collaborate with data scientists and engineers to deliver data‑driven insights and ensure data availability, quality, and performance. The role emphasizes building robust ETL/ELT pipelines, shaping data architecture, and driving governance and best practices across the analytics stack.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in data engineering, focusing on analytical data platforms.
• Experience with cloud data warehouses (BigQuery, Snowflake, Redshift).
• Strong proficiency in SQL and data modeling (star schema, dimensional modeling).
• Experience building ETL/ELT pipelines with Dagster, Airflow, dbt or equivalents.
• Programming languages such as Python, Java, or Scala.
• Data governance and data quality tools are desirable.

Responsibilities

• Design, develop, and scale an analytical data platform.
• Influence tech choices for ingestion, storage, transformation, and analysis.
• Contribute to data architecture aligned with business needs.
• Build and optimize ETL/ELT pipelines into the data warehouse.
• Develop robust data models ensuring quality, consistency, and accessibility.

Skills

Data engineering

SQL

Data modeling

ETL pipelines

Python/Java/Scala

Dagster/Airflow/dbt

Education

Bachelor's or Master's in CS/Engineering

Tools

Dagster

Apache Airflow

dbt

Job description

EvolutionIQ, Inc. in New York, NY seeks a Senior Analytics Engineer to design and scale a next‑generation analytical data platform.

You will collaborate with data scientists and engineers to deliver data‑driven insights and ensure data availability, quality, and performance. The role emphasizes building robust ETL/ELT pipelines, shaping data architecture, and driving governance and best practices across the analytics stack.