Lead Data Engineer - AWS, Databricks & Python

Next Frontier Capital; Kentucky; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive total rewards package

Health care coverage

Retirement savings plan

Tuition reimbursement

Job summary

JPMorgan Chase & Co. is seeking a Lead Data Engineer within Corporate Technology - FINTECH to advance data collection, storage, access, and analytics in a secure, scalable way.

You will be a core technical contributor maintaining critical data pipelines across multiple business functions. The role requires 3+ years in software engineering with Python and AWS, plus hands-on experience with Databricks, PySpark, and REST API development.

Qualifications

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• 3+ years of experience using Databricks, PySpark, AWS; creating ETL pipelines from scratch.
• 3+ years of experience with AWS services (Lambda, Step Functions, SQS, SNS, API Gateway, Secrets Manager, storage).
• 3+ years of software engineering and object-oriented programming, with Python and Terraform.
• Hands-on with open-source frameworks/libraries such as Apache NiFi, Apache Airflow and Autosys.
• Strong understanding of REST API development using FastAPI or equivalent frameworks.
• Advanced SQL knowledge (joins, aggregations).

Responsibilities

• Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms.
• Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way.
• Implements database backup, recovery, and archiving strategy.
• Evaluates and reports on access control processes to determine effectiveness of data asset security with minimal supervision.
• Adds to team culture of diversity, opportunity, inclusion, and respect.

Job description

JPMorgan Chase & Co. is seeking a Lead Data Engineer within Corporate Technology - FINTECH to advance data collection, storage, access, and analytics in a secure, scalable way.

You will be a core technical contributor maintaining critical data pipelines across multiple business functions. The role requires 3+ years in software engineering with Python and AWS, plus hands-on experience with Databricks, PySpark, and REST API development.