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AIG

Underwrites insurance for businesses and individuals

Data Engineer Lead

Data EngineeringConfirmed live in the last 24 hours
Full-timeParsippany-Troy Hills, NJ, USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field is required.
  • At least 7 years of hands-on data engineering experience delivering production data pipelines end-to-end is required.
  • Strong command of PySpark, Python, and SQL is required, including Spark optimization, partition management, and query performance tuning in Snowflake.
  • Hands-on experience with AWS data services, including S3, Glue, EMR, Aurora, Lambda, IAM, and CloudWatch, is required.
  • Working knowledge of architecture and design principles, including Lakehouse patterns, data modeling, and fault-tolerant ingestion, with demonstrated practical application, is required.
  • Strong analytical and problem-solving skills are required, including decomposing complex requirements, reasoning through design trade-offs, and developing practical, well-justified solutions.
  • Ability to explain technical decisions and design rationale in plain language to engineering peers and business stakeholders is required.
  • A self-motivated approach to learning and staying current with evolving tools, frameworks, and engineering best practices is required.
  • Demonstrated use of GenAI tooling, such as Claude Code CLI or Snowflake Cortex, to improve productivity or solution quality is required.

Responsibilities

  • Design, build, and operate production-grade PySpark and Python pipelines on AWS EMR, Glue, and S3 with integrated data quality checks and observability.
  • Own end-to-end delivery of data products from requirements through production within an Agile/Scrum framework, including sprint planning, CI/CD, release management, and production readiness.
  • Translate business and product requirements into technical designs, defining pipeline structure, data models, and SLAs.
  • Apply architecture and design patterns, evaluate design trade-offs, and explain the rationale to peers and stakeholders.
  • Set and enforce team engineering standards for coding conventions, data quality frameworks, reusable pipeline patterns, and observability hooks.
  • Conduct code reviews and pair with engineers on complex problems to improve the team's technical quality.
  • Use GenAI tooling, including Claude Code CLI and Snowflake Cortex, throughout development to improve coding productivity and solution quality.
  • Collaborate with product owners to refine requirements, surface trade-offs, and constructively challenge technically unworkable scope.
  • Communicate design decisions and delivery updates to engineering peers and non-technical stakeholders.
  • Mentor junior engineers through reviews, pairing, and knowledge sharing while supporting team capability and product delivery.
  • Produce technical documentation, including Architecture Decision Records, runbooks, data dictionaries, and pipeline lineage notes, as part of delivery.
  • Evaluate and drive adoption of productivity tools and best practices, setting team norms for safe and effective use.

Desired Qualifications

  • An AWS certification, such as Solutions Architect Associate or equivalent, is preferred.
  • Familiarity with insurance or financial services data domains, including claims, policy, risk, or actuarial structures, is preferred.
  • Experience writing Architecture Decision Records, design notes, or technical documentation in a collaborative engineering team is preferred.

About the Company

AIG

Underwrites insurance for businesses and individuals

AIG underwrites property and casualty insurance for businesses and individuals, covering losses from damaged assets, legal claims and personal accidents. Its commercial policies span risks such as cyberattacks, shipping losses and aviation accidents, while personal coverage includes accident and health insurance and protection for valuable homes. Brokers and agents connect clients with insurers that assess risks, set premiums and handle claims under each policy's terms. The group earns insurance premiums and investment income on assets held to meet future claims. Its operating roots date to Shanghai in 1919, and its headquarters are in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1919

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