Data Engineer

Berkley • Greenwich, CT

4d

About The Position

We are seeking a Data Engineer with strong engineering, coding, and problem‑solving skills to design, build, and operate data platforms that support actuaries, analytics, modeling, and AI‑enabled workflows. This role is suited to someone who is technically strong, comfortable working independently, and able to translate complexity into robust, well‑designed systems that others can rely on. The position emphasizes engineering rigor, high‑quality code, system reliability, and sound judgment over one‑off solutions or purely mechanical implementations. We seek someone to challenge the status quo and find better ways to build and operate data systems. You will advocate for the thoughtful application of modern data engineering, data science, and AI approaches.

Requirements

• 4–7 years of relevant data engineering, software engineering, or technical experience.
• A Master’s degree in Data Engineering or Computer Science.
• Familiarity with cloud data platforms and distributed processing frameworks (e.g., Databricks, Snowflake, Spark, or similar), and modern data engineering tooling.
• Strong programming skills, particularly in Python and SQL (including experience with distributed or batch processing frameworks such as PySpark or equivalent), with an emphasis on maintainable, testable code.
• Experience designing and operating data pipelines, data lakes/warehouses, or distributed data systems.
• Experience applying AI, machine learning, or LLM‑based tools to real engineering problems (e.g., building agents, calling model APIs, integrating AI into engineering workflows).
• Experience working with large or complex data flows and creating defensible system designs and implementation plans.
• Strong professional judgment, curiosity, and attention to detail.

Responsibilities

• Write production‑quality code for data ingestion, transformation, orchestration, and monitoring.
• Design, build, and maintain reliable, scalable data pipelines and data platforms, including batch or distributed processing workloads (e.g., Spark‑based pipelines).
• Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.
• Apply AI‑assisted engineering approaches, including LLM‑enabled tools or agents, to improve data quality, observability, documentation, and productivity.
• Identify data quality issues, bottlenecks, and failure modes; design systems that are resilient and observable.
• Stay current with data engineering and AI platform advancements, evaluate new tools, and recommend adoption where appropriate.
• Apply professional skepticism and alternate approaches to validate data correctness, lineage, and assumptions.
• Communicate system design, trade‑offs, and limitations clearly to technical and non-technical stakeholders.
• Provide support and guidance to others who are at earlier stages in their data engineering or AI journey.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees