Data Engineer: Build AI-Driven Data Pipelines & Platforms

Talentify; Greenwich (CT); On-site; USD 90,000 - 150,000; Full time

Job summary

W. R. Berkley Corporation seeks a Data Engineer to design, build, and operate data platforms supporting actuaries, analytics, and AI-enabled workflows.

The role emphasizes scalable pipelines, robust code, and system reliability, requiring independent work and rigorous engineering practices. You will collaborate with analytics teams and apply AI approaches to improve data quality and observability.

Qualifications

• 4–7 years of relevant data engineering, software engineering, or technical experience.
• Master’s degree in Data Engineering or Computer Science.
• Familiarity with cloud data platforms and distributed processing frameworks (e.g., Databricks, Snowflake, Spark).
• Strong programming skills in Python and SQL with maintainable, testable code.
• Experience designing and operating data pipelines, data lakes/warehouses, or distributed data systems.
• Experience applying AI/LLM-based tools to engineering workflows.

Responsibilities

• Write production-quality code for data ingestion, transformation, orchestration, and monitoring.
• Design, build, and maintain reliable, scalable data pipelines and data platforms (batch or Spark-based).
• Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.
• Apply AI-assisted engineering approaches to improve data quality, observability, and productivity.
• Identify data quality issues and design resilient, observable systems.
• Stay current with data engineering and AI platform advancements and evaluate new tools.

Skills

Python

SQL

Data engineering

Distributed processing

Education

Master’s degree in Data Engineering or Computer Science

Tools

Databricks

Snowflake

Spark

PySpark

Job description

W. R. Berkley Corporation seeks a Data Engineer to design, build, and operate data platforms supporting actuaries, analytics, and AI-enabled workflows.

The role emphasizes scalable pipelines, robust code, and system reliability, requiring independent work and rigorous engineering practices. You will collaborate with analytics teams and apply AI approaches to improve data quality and observability.