Data Engineer Lead

AIG PC Global Services, Inc. is seeking a Data Engineer Lead for an onsite role in Jersey City, NJ. This is a hands-on opportunity to design and run production-grade data pipelines and platforms, with the support of modern engineering practices and GenAI tooling such as Claude Code and Snowflake Cortex. If you enjoy building with strong standards, mentoring others, and keeping business stakeholders close to the work, you will fit right in.

Compensation: Competitive base salary of $125,000 to $135,000 per year, plus eligibility for a bonus based on the applicable incentive plan.

What you’ll do

• Design, build, and operate production-grade PySpark and Python pipelines on AWS EMR, Glue, and S3, including data quality checks and observability.
• Own end-to-end delivery of data products from requirements through production using an Agile/Scrum approach, including sprint planning, CI/CD, release management, and production readiness.
• Translate business and product inputs into technical designs, defining pipeline structure, data models, and SLAs.
• Apply architecture and design patterns by evaluating trade-offs and explaining the rationale to peers and stakeholders.
• Set and enforce engineering standards across the team, including coding conventions, data quality frameworks, reusable pipeline patterns, and observability hooks.
• Lead through technical quality by conducting thorough code reviews, pairing on hard problems, and raising the bar for the team.
• Use GenAI tooling throughout development, including Claude Code CLI and Snowflake Cortex, to improve solution quality and productivity.
• Partner with product owners to refine requirements, surface trade-offs, and push back constructively when scope is technically unworkable.
• Keep delivery transparent by communicating design decisions and progress to engineering and non-technical stakeholders.
• Mentor junior engineers through review, pairing, and knowledge sharing.
• Document delivery as part of the workflow by producing Architecture Decision Records (ADRs), runbooks, data dictionaries, and pipeline lineage notes.
• Evaluate and drive adoption of productivity tooling and best practices, establishing team norms for safe and effective usage.

What you bring

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
• 7+ years of hands-on data engineering experience with a consistent track record delivering production data pipelines end-to-end.
• Strong skills in PySpark, Python, and SQL, including Spark optimization, partition management, and query performance tuning in Snowflake.
• Hands-on experience with AWS data services: S3, Glue, EMR, Aurora, Lambda, IAM, and CloudWatch.
• Practical working knowledge of architecture and design principles such as lakehouse patterns and fault-tolerant ingestion.
• Strong analytical and problem-solving abilities, including decomposing complex requirements and arriving at practical, well-justified solutions.
• Clear communication skills, including the ability to explain technical decisions in plain language to both engineering peers and business stakeholders.
• Self-motivated learning mindset and genuine interest in staying current with evolving tools, frameworks, and engineering best practices.

Tools you’ll work with

PySpark, Python, AWS EMR, AWS Glue, Amazon S3, AWS Aurora, AWS Lambda, IAM, CloudWatch, SQL, Snowflake, Snowflake Cortex, Claude Code, Claude Code CLI, GenAI, Agile/Scrum, CI/CD, Architecture Decision Record (ADR)

Benefits and flexibility

• Eligible for a bonus in accordance with the terms of the applicable incentive plan.
• Comprehensive benefits package including health, wellbeing, financial security, and professional development.
• Hybrid flexibility.
• Competitive compensation.
• Created a Total Rewards Program that extends beyond time spent at work.

Culture and in-person collaboration

The Data Office is made up of builders, thinkers, and pragmatic problem-solvers. Great data engineering is treated as a team sport, supported by careful documentation, collaborative design reviews, mentoring across every level, and close partnership with business stakeholders. GenAI is encouraged as a genuine force multiplier, not a novelty.

In-person collaboration: AIG asks team members to be primarily in the office, valuing onsite collaboration as an important part of the culture.

Nice to have

• AWS certification such as Solutions Architect Associate or equivalent.
• Familiarity with insurance or financial services data (claims, policy, risk, or actuarial structures).
• Experience writing ADRs, design notes, or technical documentation in a collaborative engineering team.
• Demonstrated use of GenAI tooling (for example, Claude Code CLI or Snowflake Cortex) to improve productivity or solution quality.