Lead Data Engineer: Lakehouse & Spark Expert

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase seeks a Lead Data Engineer to join Corporate Technology. You will drive the design and delivery of data pipelines, storage, and analytics solutions in a secure, scalable environment on Databricks Lakehouse hosted in AWS.

You will lead multi-team delivery, mentor engineers, optimize Spark/Delta workloads, and implement robust governance and CI/CD practices across data platforms.

Qualifications

• Architect the lake house: design bronze/silver/gold layers and domain data products.
• Deliver scalable ingestion from AWS sources into Databricks (batch + streaming).
• Build maintainable pipelines with DLT or Jobs, with tests and docs.
• Operational excellence: productionize workloads, retries, checkpointing, and safe re-runs.
• Governance by design: least privilege, data classification, auditing, lineage/metadata.

Responsibilities

• Lead multi-team delivery and architecture for data platforms.
• Operate Databricks Lakehouse hosted on AWS, ensuring security and reliability.
• Tune Spark/Delta workloads and manage cluster sizing and costs.
• Implement governance controls (Unity Catalog, permissions, credential passthrough).
• Drive design reviews, mentoring, and cross-functional collaboration.
• Develop and maintain CI/CD pipelines and IaC (Terraform).
• Provide monitoring, incident response, RCA, and SLO/SLA management.

Skills

Databricks

Spark

AWS

Delta Lake

Data governance

CI/CD

Terraform

Mentoring

Tools

Databricks Lakehouse

Delta Live Tables

Databricks Workflows

AWS data lake

Job description

JPMorganChase seeks a Lead Data Engineer to join Corporate Technology. You will drive the design and delivery of data pipelines, storage, and analytics solutions in a secure, scalable environment on Databricks Lakehouse hosted in AWS.

You will lead multi-team delivery, mentor engineers, optimize Spark/Delta workloads, and implement robust governance and CI/CD practices across data platforms.